John Nash: game theory

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pages: 998 words: 211,235

A Beautiful Mind by Sylvia Nasar

"Robert Solow", Al Roth, Albert Einstein, Andrew Wiles, Brownian motion, business cycle, cognitive dissonance, Columbine, experimental economics, fear of failure, Gunnar Myrdal, Henri Poincaré, invisible hand, Isaac Newton, John Conway, John Nash: game theory, John von Neumann, Kenneth Arrow, Kenneth Rogoff, linear programming, lone genius, longitudinal study, market design, medical residency, Nash equilibrium, Norbert Wiener, Paul Erdős, Paul Samuelson, prisoner's dilemma, RAND corporation, Ronald Coase, second-price auction, Silicon Valley, Simon Singh, spectrum auction, The Wealth of Nations by Adam Smith, Thorstein Veblen, upwardly mobile, zero-sum game

A decline in measured intelligence within a short time of the onset of schizophrenia has been documented in a series of studies. Jed Wyatt, personal communication, 6.97. 4. Letter from John Nash to Donald Spencer, undated, spring 1961. 5. Interviews with Armand Borel, 3.1.96, and Atle Selberg, 1.23.96. 6. Letter from Atle Selberg to John Nash, 9.25.61; letter from Robert Oppenheimer to John Nash, 10.3.61. 7. John Nash, membership application, 7.17.61, Institute for Advanced Study Archive. 8. Letter from J. Nash to D. Spencer. 9. Shlomo Sternberg, interview, 3.5.96. Also postcards from John Nash to Virginia Nash, 8.1.61 and 8.3.61. 10. Alicia Nash, interview, 8.15.96. 11. Interviews with John Danskin, 10.19.95, and Odette Larde, 12.7.95. 12. O. Larde, interview. 13. “Recent Advances in Game Theory,” Princeton, October 4–6, 1961. 14. Reinhard Selten, professor of economics, University of Bonn, interview, 6.27.95. 15.

Leonard, “From Parlor Games to Social Science: Von Neumann, Morgenstern and the Creation of Game Theory, 1928–1944,” Journal of Economic Literature (1995). 16. See, for example, Harold Kuhn, ed., Classics in Game Theory (Princeton: Princeton University Press, 1997); John Eatwell, Murray Milgate, and Peter Newman, The New Palgrave: Game Theory (New York: Norton, 1987); Avinash K. Dixit and Bam J. Nalebuff, Thinking Strategically (New York: Norton, 1991). 17. Robert J. Leonard, “Reading Cournot, Reading Nash: The Creation and Stabilization of the Nash Equilibrium,” The Economic Journal (May 1994), pp. 492–511; Martin Shubik, “Antoine Augustin Cournot,” in Eatwell, Milgate, and Newman, op. cit., pp. 117–28. 18. Joseph Baratta, historian, interview, 6.12.97. 19. John Nash, “Non-Cooperative Games,” Ph.D. thesis, Princeton University Press (May 1950).

Nash was in Seattle in February of 1967, apparently for a month. Letter from John Nash to Virginia Nash, 2.67. 16. Klee, interview. 17. This scene is reconstructed on the basis of recollections from Martha Nash Legg, interview, 9.2.95. 18. Postcard from John Nash to Virginia and John Nash, Sr., 7.12.56. 19. Jerome Neuwirth, interview, 5.21.97. 20. Jacob Bricker, interview, 5.22.97. 29: Death and Marriage 1. Postcard from John Nash to Virginia and John Nash, Sr., 8.11.56. 2. Ibid., 9.18.56. 3. Elizabeth Hardwick, “Boston: A Lost Ideal,” Harper’s, December 1959, quoted in Paul Mariani, Lost Puritan: A Life of Robert Lowell (New York: Norton, 1994), p. 271. 4. Postcards from John Nash to Virginia and John Nash, Sr., 8.53, 9.53, 12.2.53, 1.2.55. 5. Martha Nash Legg, interview, 3.29.96. 6.


pages: 323 words: 100,772

Prisoner's Dilemma: John Von Neumann, Game Theory, and the Puzzle of the Bomb by William Poundstone

Albert Einstein, anti-communist, cuban missile crisis, Douglas Hofstadter, Frank Gehry, From Mathematics to the Technologies of Life and Death, Jacquard loom, John Nash: game theory, John von Neumann, Kenneth Arrow, means of production, Monroe Doctrine, mutually assured destruction, Nash equilibrium, Norbert Wiener, RAND corporation, Richard Feynman, statistical model, the market place, zero-sum game

Many of the social scientists hired or consulted were economists who had fallen under the spell of game theory. It was at RAND rather than in the groves of academia that game theory was nurtured in the years after von Neumann and Morgenstern’s book. In late 1940s and early 1950s, few of the biggest names of game theory and allied fields didn’t work for RAND, either full-time or as consultants. Besides von Neumann, RAND employed Kenneth Arrow, George Dantzig, Melvin Dresher, Merrill Flood, R. Duncan Luce, John Nash, Anatol Rapoport, Lloyd Shapley, and Martin Shubik—nearly all of whom were there at the same time. It is difficult to think of any other scientific field in which talent was concentrated so exclusively at one institution. Most of the above workers had left by 1960, but the RAND diaspora continued to dominate game theory throughout the academic world.

In recent years, his interests have included the mathematics of voting. He has explored, and attempted to popularize, voting systems that more fairly represent minority interests. John Nash became increasingly paranoid. He would pester his colleagues with peculiar ideas for tightening security at RAND. He was eventually committed to a psychiatric hospital for treatment. He recovered and joined the Institute for Advanced Study. CRITICISM OF GAME THEORY Views on game theory were changing. A decade after the publication of Theory of Games and Economic Behavior, there was a correction to the early euphoria. Game theory was deprecated, distrusted, even reviled. To many, game theory, ever intertwined with the figure of John von Neumann, appeared to encapsulate a callous cynicism about the fate of the human race. A few examples will show the severity of this reappraisal.

The only reason you came to that dealership was to get the advertised car. Now that they don’t have it, you have to wonder if you might not have been better off going to a different dealer. In game theory you generally commit to a strategy on the basis of a single potential outcome (a maximin or Nash equilibrium). If your opponent doesn’t do as game theory advocates, you may find that you could have done better with a different strategy. One of the first experimental challenges of game theory was a set of studies done at the RAND Corporation in 1952 and 1954. The research team, which included John Nash, tried to establish or refute the applicability of von Neumann’s n-person game theory. In the RAND experiments, four to seven people sat around a table. They played a “game” mimicking the general n-person game of von Neumann’s theory.


pages: 453 words: 111,010

Licence to be Bad by Jonathan Aldred

"Robert Solow", Affordable Care Act / Obamacare, Albert Einstein, availability heuristic, Ayatollah Khomeini, Benoit Mandelbrot, Berlin Wall, Black Swan, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, Cass Sunstein, clean water, cognitive dissonance, corporate governance, correlation does not imply causation, cuban missile crisis, Daniel Kahneman / Amos Tversky, Donald Trump, Douglas Engelbart, Douglas Engelbart, Edward Snowden, Fall of the Berlin Wall, falling living standards, feminist movement, framing effect, Frederick Winslow Taylor, From Mathematics to the Technologies of Life and Death, full employment, George Akerlof, glass ceiling, Intergovernmental Panel on Climate Change (IPCC), invisible hand, Isaac Newton, Jeff Bezos, John Nash: game theory, John von Neumann, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, meta analysis, meta-analysis, Mont Pelerin Society, mutually assured destruction, Myron Scholes, Nash equilibrium, Norbert Wiener, nudge unit, obamacare, offshore financial centre, Pareto efficiency, Paul Samuelson, plutocrats, Plutocrats, positional goods, profit maximization, profit motive, race to the bottom, RAND corporation, rent-seeking, Richard Thaler, ride hailing / ride sharing, risk tolerance, road to serfdom, Robert Shiller, Robert Shiller, Ronald Coase, Ronald Reagan, Skype, Social Responsibility of Business Is to Increase Its Profits, spectrum auction, The Nature of the Firm, The Wealth of Nations by Adam Smith, transaction costs, trickle-down economics, Vilfredo Pareto, wealth creators, zero-sum game

Game theory can tell us the smart way to behave in some economic and social contexts – that is, contexts in which every player knows that every player is well versed in game theory, as if they have a state-of-the-art textbook in hand. So if a chess Grandmaster is playing another chess Grandmaster, then both of them might reasonably assume their opponent has a sophisticated knowledge of game theory. Such a defence of game theory is (a bit) less useless than it seems. On 5th December 1994, the day John Nash left America for Stockholm to collect his Nobel Prize, Vice-President Gore was announcing the ‘greatest auction ever’ – an auction of airwave frequency spectrum licences to be used by mobile phones. Auctions are a type of game, and this auction was carefully designed using the latest game theory. When the auction closed in March 1995, the US government was delighted: it had received more than $7 billion in bids.

Poor Ronald Coase – he didn’t even get to control the spelling of ‘Coasean world’, let alone what it means. 4 The Government Enemy In the early 1950s John von Neumann and John Nash were not the only geniuses associated with the RAND Corporation. RAND was the incubator for another intellectual revolution, as significant as game theory but completely independent of it. And this time the genius behind it was a lowly intern. The earliest and most enthusiastic adopters of game theory had been the military analysts at RAND, who wanted to use its powerful mathematical tools to outwit the Soviets in Cold War nuclear strategizing. But logical rigour was everything to the RAND thinkers, and by 1948 a possible flaw had been spotted in the logic of analysing nuclear conflict in game-theoretic terms. Whether the game is Scrabble or Armageddon, game theory views the players in just the same way, as rational individuals.

Given von Neumann’s mathematical ambitions for social science, it was ironic that what finally propelled game theory beyond RAND and university maths departments was not maths but a story. Albert Tucker was John Nash’s PhD supervisor. In May 1950, just after persuading his wayward student not to abandon his PhD on game theory, Tucker was asked to talk about the new theory to a group of psychologists. Since his audience did not know the theory or the maths, Tucker decided to present a game he had learned about from some RAND researchers in the form of a little story. He called it the Prisoner’s Dilemma. Two members of a criminal gang have been imprisoned separately. The police have enough evidence to convict them both of a minor crime, but not the major one that they suspect them of committing. So they offer each prisoner the following deal: confess and implicate your partner and you receive immunity from prosecution while your former partner will be hit with a ten-year sentence.


pages: 360 words: 85,321

The Perfect Bet: How Science and Math Are Taking the Luck Out of Gambling by Adam Kucharski

Ada Lovelace, Albert Einstein, Antoine Gombaud: Chevalier de Méré, beat the dealer, Benoit Mandelbrot, butterfly effect, call centre, Chance favours the prepared mind, Claude Shannon: information theory, collateralized debt obligation, correlation does not imply causation, diversification, Edward Lorenz: Chaos theory, Edward Thorp, Everything should be made as simple as possible, Flash crash, Gerolamo Cardano, Henri Poincaré, Hibernia Atlantic: Project Express, if you build it, they will come, invention of the telegraph, Isaac Newton, Johannes Kepler, John Nash: game theory, John von Neumann, locking in a profit, Louis Pasteur, Nash equilibrium, Norbert Wiener, p-value, performance metric, Pierre-Simon Laplace, probability theory / Blaise Pascal / Pierre de Fermat, quantitative trading / quantitative finance, random walk, Richard Feynman, Ronald Reagan, Rubik’s Cube, statistical model, The Design of Experiments, Watson beat the top human players on Jeopardy!, zero-sum game

As Ferguson discovered when he applied game theory to poker, sometimes an idea that seems unremarkable to scientists can prove extremely powerful when used in a different context. While the fiery debate between von Neumann and Fréchet sparked and crackled, John Nash was busy finishing his doctorate at Princeton. By establishing the Nash equilibrium, he had managed to extend von Neumann’s work, making it applicable to a wider number of situations. Whereas von Neumann had looked at zero-sum games with two players, Nash showed that optimal strategies exist even if there are multiple players and uneven payoffs. But knowing perfect strategies always exist is just the start for poker players. The next problem is working out how to find them. MOST PEOPLE WHO HAVE a go at creating poker bots don’t rummage through game theory to find optimal strategies.

In Marihuana: A Signal of Misunderstanding (report of the National Commission on Marihuana and Drug Abuse, 1972). http://www.druglibrary.org/schaffer/library/studies/nc/nc2b.htm. 136Far from hurting tobacco companies’ profits: McAdams, David. Game-Changer: Game Theory and the Art of Transforming Strategic Situations (New York: W. W. Norton, 2014), 61. 137Yet tobacco revenues held steady: Hamilton, James. “The Demand for Cigarettes: Advertising, the Health Scare, and the Cigarette Advertising Ban.” Review of Economics and Statistics 54, no. 4 (1972). 137“Mr. Nash is nineteen years old”: The letter was posted online by Princeton University after John Nash’s death in 2015. It went viral. 138Despite his prodigious academic record: Halmos, Paul. “The Legend of John von Neumann.” American Mathematical Monthly 8 (1973): 382–394. 138“Real life consists of bluffing”: Harford, Tim. “A Beautiful Theory.” Forbes, December 14, 2006. http://www.forbes.com/2006/12/10/business-game-theory-tech-cx_th_games06_1212harford.html.

Economists refer to such a situation—where each person is making the best decision possible given the choices made by others—as a “Nash equilibrium.” Spending would rise further and further until this costly game stopped. Or somebody forced it to stop. Congress finally banned tobacco ads from television in January 1971. One year later, the total spent on cigarette advertising had fallen by over 25 percent. Yet tobacco revenues held steady. Thanks to the government, the equilibrium had been broken. JOHN NASH PUBLISHED HIS first papers on game theory while he was a PhD student at Princeton. He’d arrived at the university in 1948, after being awarded a scholarship on the strength of his undergraduate tutor’s reference, a two-sentence letter that read, “Mr. Nash is nineteen years old and is graduating from Carnegie Tech in June. He is a mathematical genius.” During the next two years, Nash worked on a version of the “prisoner’s dilemma.”


pages: 422 words: 131,666

Life Inc.: How the World Became a Corporation and How to Take It Back by Douglas Rushkoff

addicted to oil, affirmative action, Amazon Mechanical Turk, anti-globalists, banks create money, big-box store, Bretton Woods, car-free, Charles Lindbergh, colonial exploitation, Community Supported Agriculture, complexity theory, computer age, corporate governance, credit crunch, currency manipulation / currency intervention, David Ricardo: comparative advantage, death of newspapers, don't be evil, Donald Trump, double entry bookkeeping, easy for humans, difficult for computers, financial innovation, Firefox, full employment, global village, Google Earth, greed is good, Howard Rheingold, income per capita, invention of the printing press, invisible hand, Jane Jacobs, John Nash: game theory, joint-stock company, Kevin Kelly, Kickstarter, laissez-faire capitalism, loss aversion, market bubble, market design, Marshall McLuhan, Milgram experiment, moral hazard, mutually assured destruction, Naomi Klein, negative equity, new economy, New Urbanism, Norbert Wiener, peak oil, peer-to-peer, place-making, placebo effect, Ponzi scheme, price mechanism, price stability, principal–agent problem, private military company, profit maximization, profit motive, race to the bottom, RAND corporation, rent-seeking, RFID, road to serfdom, Ronald Reagan, short selling, Silicon Valley, Simon Kuznets, social software, Steve Jobs, Telecommunications Act of 1996, telemarketer, The Wealth of Nations by Adam Smith, Thomas L Friedman, too big to fail, trade route, trickle-down economics, union organizing, urban decay, urban planning, urban renewal, Vannevar Bush, Victor Gruen, white flight, working poor, Works Progress Administration, Y2K, young professional, zero-sum game

In every single experiment, however, instead of making choices in the self-interested way that Rand expected, the secretaries chose to cooperate. This didn’t deter John Nash, the Rand mathematician portrayed by Russell Crowe in the movie A Beautiful Mind, from continuing to develop game scenarios for the government based on presumptions of fear and self-interest. An undiagnosed paranoid schizophrenic, Nash blamed the failed experiments on the secretaries themselves. They were unfit subjects, incapable of following the simple “ground rules” that they should strategize selfishly. Nash remained committed to the rather paranoid view that human beings are suspicious creatures, constantly making strategic assessments about one another and calculating how to gain a competitive advantage in any situation. Game theory worked quite well in poker, anyway, from which it originated. And what better model existed for the high-stakes nuclear standoff between the United States and the U.S.S.R.?

Freakonomics, the runaway best seller and its follow-up New York Times Magazine column, applied this model of “rational utility-maximization” to human behaviors ranging from drug dealing to cheating among sumo wrestlers. Economics explained everything with real numbers, and the findings were bankable. Even better, the intellectual class had a new way of justifying its belief that people really do act the way they’re supposed to in one of John Nash’s game scenarios. Ironically, while the intelligentsia were using social evolution to confirm laissez-faire capitalism to one another, the politicians promoting these policies to the masses were making the same sale through creationism. Right-wing conservatives turned to fundamentalist Christians to promote the free-market ethos, in return promising lip service to hot-button Christian issues such as abortion and gay marriage.

The principles of the intentionally corporatized marketplace are not embedded in the human genome, nor is self-interested behavior an innate human instinct. If anything, it’s the other way around: a landscape defined by the competitive market will promote self-interested behavior. It’s the surest path to a corporatist society. Maybe that was the objective all along. Central Currency The economy in which we all participate is no more natural than the game scenarios John Nash set up to test the Rand Corporation’s secretaries. It is a model for human interaction, based on a set of false assumptions about human behavior. Even if we buy the proposition that people act as self-interestedly as they possibly can, we must accept the reality that people’s actual choices don’t correspond with their own financial well-being. They do not act in their own best financial interests.


pages: 1,535 words: 337,071

Networks, Crowds, and Markets: Reasoning About a Highly Connected World by David Easley, Jon Kleinberg

Albert Einstein, AltaVista, clean water, conceptual framework, Daniel Kahneman / Amos Tversky, Douglas Hofstadter, Erdős number, experimental subject, first-price auction, fudge factor, George Akerlof, Gerard Salton, Gerard Salton, Gödel, Escher, Bach, incomplete markets, information asymmetry, information retrieval, John Nash: game theory, Kenneth Arrow, longitudinal study, market clearing, market microstructure, moral hazard, Nash equilibrium, Network effects, Pareto efficiency, Paul Erdős, planetary scale, prediction markets, price anchoring, price mechanism, prisoner's dilemma, random walk, recommendation engine, Richard Thaler, Ronald Coase, sealed-bid auction, search engine result page, second-price auction, second-price sealed-bid, Simon Singh, slashdot, social web, Steve Jobs, stochastic process, Ted Nelson, The Market for Lemons, The Wisdom of Crowds, trade route, transaction costs, ultimatum game, Vannevar Bush, Vickrey auction, Vilfredo Pareto, Yogi Berra, zero-sum game

INFORMATION NETWORKS, HYPERTEXT, AND ASSOCIATIVE MEMORY389 Nash Game Equilibrium Theory John Forbes Nash RAND A Beautiful Mind (film) Apollo 13 Conspiracy Ron Howard (film) Theories NASA Figure 13.4: The cross-references among a set of articles in an encyclopedia forms another kind of information network that can be represented as a directed graph. The figure shows the cross-references among a set of Wikipedia articles on topic in game theory, and their connections to related topics including popular culture and government agencies. how it’s possible to get from the article on Nash Equilibrium to the article on NASA (the U.S. National Aeronautics and Space Administration) by passing through articles on John Nash (the creator of Nash equilibrium), A Beautiful Mind (a film about John Nash’s life), Ron Howard (the director of A Beautiful Mind), Apollo 13 (another film directed by Ron Howard), and finally on to the article about NASA (the U.S. government agency that managed the real Apollo 13 space mission).

Review of Economic Studies, 67:57–78, 2000. [304] Elchanan Mossel and Sebastien Roch. On the submodularity of influence in social networks. In Proc. 39th ACM Symposium on Theory of Computing, 2007. [305] Roger Myerson. Incentive compatibility and the bargaining problem. Econometrica, 47:61–73, 1979. [306] John Nash. The bargaining problem. Econometrica, 18:155–162, 1950. [307] John Nash. Equilibrium points in n-person games. Proc. Natl. Acad. Sci. USA, 36:48–49, 1950. [308] John Nash. Non-cooperative games. Annals of Mathematics, 54:286–295, 1951. [309] National Research Council Committee on Technical and Privacy Dimensions of Information for Terrorism Prevention and Other National Goals. Protecting Individual Privacy in the Struggle Against Terrorists: A Framework for Program Assessment.

Is this list of strategies a Nash equilibrium of the simultaneous move game between the three players? 218 CHAPTER 6. GAMES Chapter 7 Evolutionary Game Theory In Chapter 6, we developed the basic ideas of game theory, in which individual players make decisions, and the payoff to each player depends on the decisions made by all. As we saw there, a key question in game theory is to reason about the behavior we should expect to see when players take part in a given game. The discussion in Chapter 6 was based on considering how players simultaneously reason about what the other players may do. In this chapter, on the other hand, we explore the notion of evolutionary game theory, which shows that the basic ideas of game theory can be applied even to situations in which no individual is overtly reasoning, or even making explicit decisions.


Gaming the Vote: Why Elections Aren't Fair (And What We Can Do About It) by William Poundstone

affirmative action, Albert Einstein, business cycle, Debian, desegregation, Donald Trump, en.wikipedia.org, Everything should be made as simple as possible, global village, guest worker program, hiring and firing, illegal immigration, invisible hand, jimmy wales, John Nash: game theory, John von Neumann, Kenneth Arrow, manufacturing employment, Nash equilibrium, Paul Samuelson, Pierre-Simon Laplace, prisoner's dilemma, Ralph Nader, RAND corporation, Ronald Reagan, Silicon Valley, slashdot, the map is not the territory, Thomas Bayes, transcontinental railway, Unsafe at Any Speed, Y2K

'The idea was that because of the new nature of warfare, particularly the bomb, all the old views were wrong ... It was an invitation to take a very wild point of view." RAND took pride in hiring a diverse group of specialists and encouraging everyone to talk to one another. Over the years, RAND's scholars and consultants have ranged from John Nash to Condoleezza Rice. In its first decade, however, the guiding spirit of the place was unquestionably John von Neumann. "Everyone sat up in great awe" when von Neumann spoke, Arrow said. Politically, von Neumann was conservative and a hawk. He believed that game theory provided useful models for nuclear deterrence and arms races. RAND's people pondered questions such as would the Soviet Union launch a first strike against the United States if it meant losing twenty million people in the counterattack? Would building a hydrogen bomb enhance or diminish U.S. security?

Bad Santa 201 Donald Saari • Kris Kringle • the nobody problem • rigged elections • Peter Fishburn· Samuel Merrill III • Jill Van Newenhizen • indeterminacy· rebuttals and counter-rebuttals • Unsophisticated Voter System· unmitigated evil • symmetry • polyhedra • behavioral assumptions I find to be >'ery dangerous • Mr. Mediocre· Thomas Edison· electrocuted dogs· "'President Perot" • Alexander Tabarrok • '"Buddy" Roemer· how to buy kitchen cabinets· "'wherever you go, there you are"· polls· chameleon on a mirror· bandwagon effect· Jesse Ventura· Roger B. Myerson· John Nash· self-interest· bullet voting· Terry Sanford· air bags· Burr's dilemma , Contents 13. Last Man Standing 219 Orange County· John Wayne· American machismo· the Condorcet winner· Linux • Markus Schulze· CSSD • Wikipedia • trolls· Queen Elizabeth· Kim Jongil • sarcasm· simplicity· Ka-Ping Yee· Microsoft Windows· manipulative behavior • how ro prevent carjacking· Mathematics Awareness Week • lain Mclean· permanent pointlessness 231 14.

One of those present, Roger B. Myerson, saw a clever way of treating the problem. Myerson and Weber ended up collaborating on a 1993 article, "A Theory of Voting Equilibria." In Weber's words, 'This is the paper that, I believe, makes the strongest theoretical case for approval voting." The publication invokes another idea with roots in the cold war, the "Nash equilibrium." As a RAND consultant, mathematician John Nash (of A Beautiful Mind fame) proposed a particular kind of solution to the "games" of nuclear deterrence or voting or anything else, A Nash equilibrium is an outcome where everyone is satisfied with his or her decision, given what everyone else did. No one has any regrets about doing what he did. In the case of voting, this means that all the voters are happy with the way they voted (though not necessarily happy with the election's outcome).


pages: 482 words: 125,973

Competition Demystified by Bruce C. Greenwald

additive manufacturing, airline deregulation, AltaVista, asset allocation, barriers to entry, business cycle, creative destruction, cross-subsidies, deindustrialization, discounted cash flows, diversified portfolio, Everything should be made as simple as possible, fault tolerance, intangible asset, John Nash: game theory, Nash equilibrium, Network effects, new economy, oil shock, packet switching, pets.com, price discrimination, price stability, selective serotonin reuptake inhibitor (SSRI), shareholder value, Silicon Valley, six sigma, Steve Jobs, transaction costs, yield management, zero-sum game

Given the stability of expectations, no competitor can improve its outcome by choosing an alternative course of action. The two conditions work together; if no competitor has a motive to change its current course of action (stability of behavior), then no change will occur, confirming the stability of expectations. This concept of the likely outcome to a competitive situation is referred to in game theory as a “Nash equilibrium,” after its developer John Nash of A Beautiful Mind and Nobel Prize fame. In the Lowe’s–Home Depot example, imagine that the current outcome has Lowe’s at $115 per basket, Home Depot at $105 per basket (box C). If Lowe’s expects Home Depot to keep its price at $105, Lowe’s can improve its position by lowering its price to match Home Depot. With both at $105, they split the market and Lowe’s gross profit rises from $120 to $150.

INDIVIDUAL RATIONALITY The first condition of fairness is that no firm in a cooperative arrangement should receive less than it could obtain in a noncooperative setting. Clearly, a company that can do better by not cooperating is not going to continue to cooperate. In the language of formal game theory, this condition is referred to as “individual rationality.” Unless it makes sense for each firm to cooperate, meaning that each firm does at least as well by cooperating as by refusing to cooperate, then cooperation will not be sustainable. In this sense, the original division of the spoils will not be fair. Because of the fairness condition, it is important to consider the outcome that firms can achieve when they do not cooperate. In John Nash’s term, these are “threat point” outcomes, the “threat” being noncooperation and a myopic pursuit of one’s individual goals. In the language of negotiation theory, the same outcome is referred to by the acronym BATNA—the best alternative to a negotiated agreement.

The roles that the company would play within a cooperative configuration, and the market positions it would occupy, highlight the specific competences that the company brings to the industry and thus the areas in which it should focus its efforts. Only after it has made these decisions is it time to turn to the question of what rewards it might reasonably expect to earn from these focused activities. UTILIZING “FAIRNESS” PRINCIPLES TO DIVIDE THE SPOILS WHILE SUSTAINING COOPERATION The mathematician John Nash won the Nobel Prize in Economics for, among a few other things, initiating work on the principles of “fairness” for determining the division of rewards in an industry that has achieved a stable cooperative organization (a cooperative equilibrium). Other economists have built on Nash’s efforts, so that now the principles are well established. Here we will focus on three: individual rationality, symmetry, and linear invariance.


pages: 503 words: 131,064

Liars and Outliers: How Security Holds Society Together by Bruce Schneier

airport security, barriers to entry, Berlin Wall, Bernie Madoff, Bernie Sanders, Brian Krebs, Broken windows theory, carried interest, Cass Sunstein, Chelsea Manning, commoditize, corporate governance, crack epidemic, credit crunch, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, David Graeber, desegregation, don't be evil, Double Irish / Dutch Sandwich, Douglas Hofstadter, experimental economics, Fall of the Berlin Wall, financial deregulation, George Akerlof, hydraulic fracturing, impulse control, income inequality, invention of agriculture, invention of gunpowder, iterative process, Jean Tirole, John Nash: game theory, joint-stock company, Julian Assange, longitudinal study, mass incarceration, meta analysis, meta-analysis, microcredit, moral hazard, mutually assured destruction, Nate Silver, Network effects, Nick Leeson, offshore financial centre, patent troll, phenotype, pre–internet, principal–agent problem, prisoner's dilemma, profit maximization, profit motive, race to the bottom, Ralph Waldo Emerson, RAND corporation, rent-seeking, RFID, Richard Thaler, risk tolerance, Ronald Coase, security theater, shareholder value, slashdot, statistical model, Steven Pinker, Stuxnet, technological singularity, The Market for Lemons, The Nature of the Firm, The Spirit Level, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, too big to fail, traffic fines, transaction costs, ultimatum game, UNCLOS, union organizing, Vernor Vinge, WikiLeaks, World Values Survey, Y2K, zero-sum game

Many researchers Sylvia Nasar (2001), A Beautiful Mind: The Life of Mathematical Genius and Nobel Laureate John Nash, Simon & Schuster. John Nash (2008), “The Agencies Method for Modeling Coalitions & Cooperations in Games,” International Game Theory Review, 10:539–64. Robert Axelrod and William D. Hamilton (1981), “The Evolution of Cooperation,” Science, 211:1390–6. Robert Axelrod (1984), The Evolution of Cooperation, Basic Books. open grazing pasture Garrett Hardin (1968), “The Tragedy of the Commons,” Science, 162:1243–8. Chapter 6 predictably irrational Dan Ariely (2008), Predictably Irrational: The Hidden Forces That Shape our Decisions, Harper Perennial. Cuban Missile Crisis Steven J. Brams (24 Jan 2001), “Game Theory and the Cuban Missile Crisis,” Plus Magazine. worst in people Morton Deutsch and Robert M.

How else can you explain that so many of our Facebook pages include people we would never have even considered talking to in high school, and yet we help water their imaginary plants? Chapter 5 (1) The Prisoner's Dilemma was originally framed in the 1950s by Merrill Flood and Melvin Dresher at the RAND Corporation, and was named several years later by Albert Tucker.Many researchers have informed and analyzed this game, most famously John Nash and then Robert Axelrod, who used it to help explain the evolution of cooperation. (2) I should probably explain about Alice and Bob. Cryptographers—and I started as a cryptographer—name the two actors in any security discussion Alice and Bob. To us, anyone we don't know is either Alice or Bob. If you meet me, don't be surprised if I call you Alice or Bob. (3) As stylized as the story is, this sort of thing is not uncommon.

Spammers do better if they don't clog e-mail to the point where no one uses it anymore, and rogue banks are more profitable if they don't crash the entire economy. All parasites do better if they don't destroy whatever system they've latched themselves onto. Parasites thrive only if they don't thrive too well. There's a clever model from game theory that illustrates this: the Hawk-Dove game. It was invented by geneticists John Maynard Smith and George R. Price in 1971 to explain conflicts between animals of the same species. Like most game theory models, it's pretty simplistic. But what it illuminates about the real world is profound. The game works like this. Assume a population of individuals with differing survival strategies. Some cooperate and some defect. In the language of the game, the defectors are hawks. They're aggressive; they attack other individuals, and fight back if attacked.


pages: 523 words: 143,139

Algorithms to Live By: The Computer Science of Human Decisions by Brian Christian, Tom Griffiths

4chan, Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, algorithmic trading, anthropic principle, asset allocation, autonomous vehicles, Bayesian statistics, Berlin Wall, Bill Duvall, bitcoin, Community Supported Agriculture, complexity theory, constrained optimization, cosmological principle, cryptocurrency, Danny Hillis, David Heinemeier Hansson, delayed gratification, dematerialisation, diversification, Donald Knuth, double helix, Elon Musk, fault tolerance, Fellow of the Royal Society, Firefox, first-price auction, Flash crash, Frederick Winslow Taylor, George Akerlof, global supply chain, Google Chrome, Henri Poincaré, information retrieval, Internet Archive, Jeff Bezos, Johannes Kepler, John Nash: game theory, John von Neumann, Kickstarter, knapsack problem, Lao Tzu, Leonard Kleinrock, linear programming, martingale, Nash equilibrium, natural language processing, NP-complete, P = NP, packet switching, Pierre-Simon Laplace, prediction markets, race to the bottom, RAND corporation, RFC: Request For Comment, Robert X Cringely, Sam Altman, sealed-bid auction, second-price auction, self-driving car, Silicon Valley, Skype, sorting algorithm, spectrum auction, Stanford marshmallow experiment, Steve Jobs, stochastic process, Thomas Bayes, Thomas Malthus, traveling salesman, Turing machine, urban planning, Vickrey auction, Vilfredo Pareto, Walter Mischel, Y Combinator, zero-sum game

What makes this equilibrium stable is that, once both players adopt this 1⁄3 - 1⁄3 - 1⁄3 strategy, there is nothing better for either to do than stick with it. (If we tried playing, say, more rock, our opponent would quickly notice and start playing more paper, which would make us play more scissors, and so forth until we both settled into the 1⁄3 - 1⁄3 - 1⁄3 equilibrium again.) In one of the seminal results in game theory, the mathematician John Nash proved in 1951 that every two-player game has at least one equilibrium. This major discovery would earn Nash the Nobel Prize in Economics in 1994 (and lead to the book and film A Beautiful Mind, about Nash’s life). Such an equilibrium is now often spoken of as the “Nash equilibrium”—the “Nash” that Dan Smith always tries to keep track of. On the face of it, the fact that a Nash equilibrium always exists in two-player games would seem to bring us some relief from the hall-of-mirrors recursions that characterize poker and many other familiar contests.

As we’ve seen, it’s not enough for a problem to have a solution if that problem is intractable. In a game-theory context, knowing that an equilibrium exists doesn’t actually tell us what it is—or how to get there. As UC Berkeley computer scientist Christos Papadimitriou writes, game theory “predicts the agents’ equilibrium behavior typically with no regard to the ways in which such a state will be reached—a consideration that would be a computer scientist’s foremost concern.” Stanford’s Tim Roughgarden echoes the sentiment of being unsatisfied with Nash’s proof that equilibria always exist. “Okay,” he says, “but we’re computer scientists, right? Give us something we can use. Don’t just tell me that it’s there; tell me how to find it.” And so, the original field of game theory begat algorithmic game theory—that is, the study of theoretically ideal strategies for games became the study of how machines (and people) come up with strategies for games.

On the contrary, it represents a situation in which the dice are as loaded against the emergence of cooperation as they could possibly be.”* Well, if the rules of the game force a bad strategy, maybe we shouldn’t try to change strategies. Maybe we should try to change the game. This brings us to a branch of game theory known as “mechanism design.” While game theory asks what behavior will emerge given a set of rules, mechanism design (sometimes called “reverse game theory”) works in the other direction, asking: what rules will give us the behavior we want to see? And if game theory’s revelations—like the fact that an equilibrium strategy might be rational for each player yet bad for everyone—have proven counterintuitive, the revelations of mechanism design are even more so. Let’s return you and your bank-robbing co-conspirator to the jail cell for another go at the prisoner’s dilemma, with one crucial addition: the Godfather.


pages: 88 words: 25,047

The Mathematics of Love: Patterns, Proofs, and the Search for the Ultimate Equation by Hannah Fry

Brownian motion, John Nash: game theory, linear programming, Nash equilibrium, Pareto efficiency, recommendation engine, Skype, statistical model

Say you’re at a party with a group of single friends, all trying to decide how best to boost your chances of meeting someone. Should you sit back and wait for them to come to you, or walk right up to the prettiest partygoer, risking a humiliating rejection? And who should you approach to give you the best chance of success? If we all go for the blonde Anybody who has seen the 2001 film A Beautiful Mind might think that maths already has the answer. The film follows the life of mathematics superstar John Nash and includes some dramatized explanations of his major mathematical breakthroughs. In one famous scene, Nash and his three charming gentlemen friends spot a group of five women in a bar: four brunettes and one particularly beautiful blonde. All of the men are immediately drawn to the blonde. But, rather than all rushing to shower her with attention, Nash argues for a different tactic. Strategically, he suggests they would all do better by ignoring the blonde and aiming for her four brunette friends instead: If we all go for the blonde, we block each other and not a single one of us is going to get her.

This is the motivation of international bestsellers like The Game and The Rules of the Game, which have paved the way for men and women to treat each other as conquests. And both are based on a single idea: how to exploit stereotypes to try and maximize your own reward. As we’ve already seen, the mathematics of game theory can be used to beat other suitors. And if you’re looking to turn the dating game into a dating war, it is also ideally placed to provide the best strategy in a romantic contest between two opponents. A warning: game theory encourages you to exploit the weaknesses of your opponents. When applied to dating, this view comes with a slightly cynical picture of the world. As a result, the first half of this chapter will show you some of the best tenets of game theory, not the best tenets of human morality. And because they rely on exploiting the supposed differences between men and women, they don’t really work for any non-traditional or non-heterosexual couples.

The result is the eligible bachelor paradox, and it comes with a clear, if slightly harsh, take-home message: no matter how hot you are, if your goal is partnership, don’t get complacent. But before we consign ourselves to dying alone and rush out to buy a houseful of cats, it’s worth pausing and looking at these examples objectively. As neat an application of game theory as they are mathematically, they have one flawed assumption at their core: that men are trying to trick women into having sex with them and women are desperate for commitment. In reality, don’t both sexes want both? Crazily enough, I suspect there may even be some women who want sex and some men who want commitment. And thus this particular game-theory house of cards comes tumbling down. Thankfully, there are ways to use game theory that don’t require men and women to conform to stereotypes, and in particular, a formulation that can apply to many of the most common dating conundrums for every type of relationship.


pages: 389 words: 98,487

The Undercover Economist: Exposing Why the Rich Are Rich, the Poor Are Poor, and Why You Can Never Buy a Decent Used Car by Tim Harford

Albert Einstein, barriers to entry, Berlin Wall, business cycle, collective bargaining, congestion charging, Corn Laws, David Ricardo: comparative advantage, decarbonisation, Deng Xiaoping, Fall of the Berlin Wall, George Akerlof, information asymmetry, invention of movable type, John Nash: game theory, John von Neumann, Kenneth Arrow, Kickstarter, market design, Martin Wolf, moral hazard, new economy, Pearl River Delta, price discrimination, Productivity paradox, race to the bottom, random walk, rent-seeking, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Reagan, sealed-bid auction, second-price auction, second-price sealed-bid, Shenzhen was a fishing village, special economic zone, spectrum auction, The Market for Lemons, Thomas Malthus, trade liberalization, Vickrey auction

(You also receive a bad payoff if we have a head-on collision, but in game theory I don’t usually care about your payoff for its own sake. I care about your payoffs only because they help me predict your behavior.) Games are often described in just that way, using little stories or anecdotes, but these stories conceal the fact that for a game theorist, games are mathematical objects. The great game theorists are brilliant mathematicians, such as Von Neumann himself, or Nobel Prize winner John Nash, the subject of A Beautiful Mind. As in the case of all game theory, Nash’s revolutionary new way to predict a game’s outcome was an inspired application of well-understood mathematics. Von Neumann was fascinated by poker, and as he turned his mind to the game he developed mathematical tools that are not only handy for economists but for people trying to understand everything from dating to evolutionary biology or the cold war.

Losses due to internet music piracy from “Rock profits and boogie woogie blues,” May 2, 2004, BBC Online News, http://news.bbc.co.uk/1/hi/business/ 3622285.stm. Data from Robert Shiller are available at his home page, http:// aida.econ.yale.edu/~shiller/. Chapter 7 See Prisoner’s Dilemma by William Poundstone (New York: Doubleday, 1992) to find out more about Von Neumann and the use of game theory in the cold war. For an analysis of poker models by Emile Borel, Von Neumann, John Nash, and Lloyd Shapley, see chapter 12 of Ken Binmore’s textbook Fun and Games (Lexington: D. C. Heath, 1992). This is the same Ken Binmore who later went on to lead the auction design team for the UK 3G auction. The United States spectrum auctions are expertly discussed in John McMillan’s “Selling Spectrum Rights,” Journal of Economic Perspectives 8, no. 3 (Summer 1994): 145–62; also McAfee and McMillan’s “Analysing the Airwaves Auction,” Journal of Economic Perspectives 10, no. 1 (Winter 1996): 159–75.

One of the most difficult challenges of all is rooted in the very origins of game theory: it was developed by men of nearly superhuman intellect like Nash and Von Neumann. That is both its great strength and its great weakness, because for game theory to be successful, it has to provide insight into what mere mortals do. Game theory expresses the way people would act as the solution to a mathematical equation. It presumes hyperrational players who are able instantly to solve very tough problems, and this description starts to look unrealistic if game theory is to be a practical tool for explaining how real people actually behave. Nash and Von Neumann really could solve such problems instantly. The rest of us cannot. For instance, game theory tells us that chess is not worth playing because in theory its outcome is predetermined: one player can force a result.


pages: 463 words: 118,936

Darwin Among the Machines by George Dyson

Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, anti-communist, British Empire, carbon-based life, cellular automata, Claude Shannon: information theory, combinatorial explosion, computer age, Danny Hillis, Donald Davies, fault tolerance, Fellow of the Royal Society, finite state, IFF: identification friend or foe, invention of the telescope, invisible hand, Isaac Newton, Jacquard loom, James Watt: steam engine, John Nash: game theory, John von Neumann, low earth orbit, Menlo Park, Nash equilibrium, Norbert Wiener, On the Economy of Machinery and Manufactures, packet switching, pattern recognition, phenotype, RAND corporation, Richard Feynman, spectrum auction, strong AI, the scientific method, The Wealth of Nations by Adam Smith, Turing machine, Von Neumann architecture, zero-sum game

A substantial section of the 625-page book is devoted to showing how seemingly intractable situations can be rendered solvable through the assumption of coalitions among the players, and how non-zero-sum games can be reduced to zero-sum games by including a fictitious, impartial player (sometimes called Nature) in the game. Game theory was applied to fields ranging from nuclear deterrence to evolutionary biology. “The initial reaction of the economists to this work was one of great reserve, but the military scientists were quick to sense its possibilities in their field,” wrote J. D. Williams in The Compleat Strategyst, a RAND Corporation best-seller that made game theory accessible through examples drawn from everyday life.6 The economists gradually followed. When John Nash was awarded a Nobel Prize for the Nash equilibrium in 1994, he became the seventh Nobel laureate in economics whose work was influenced directly by von Neumann’s ideas. Nash and von Neumann had collaborated at RAND.

., New York: John Wiley, 1947), 2 (page citation is to the 2d edition). 3.Loren Eiseley, Darwin’s Century (New York: Doubleday, 1958), 39. 4.André-Marie Ampère, Considérations sur la théorie mathématique du jeu (Lyons, France: Frères Perisse, 1802), 3. (Author’s translation.) 5.Jacob Marschak, “Neumann’s and Morgenstern’s New Approach to Static Economics,” Journal of Political Economy 54, no. 2 (April 1946): 114. 6.J. D. Williams, The Compleat Strategyst (Santa Monica, Calif.: RAND Corporation, 1954), 216. 7.John Nash, Parallel Control, RAND Corporation Research Memorandum RM-1361, 27 August 1954, 14. 8.John von Neumann, “A Model of General Economic Equilibrium,” Review of Economic Studies 13 (1945): 1. 9.John von Neumann, The Computer and the Brain (New Haven, Conn.: Yale University Press, 1958), 79–82. 10.John von Neumann, 1948, “General and Logical Theory of Automata,” in Lloyd A. Jeffress, ed., Cerebral Mechanisms in Behavior: The Hixon Symposium (New York: Hafner, 1951), 24. 11.Stan Ulam, quoted by Gian-Carlo Rota, “The Barrier of Meaning,” Letters in Mathematical Physics 10 (1985): 99. 12.von Neumann, “Automata,” 24. 13.Stan Ulam, quoted by Rota, “The Barrier of Meaning,” 98. 14.D.

Von Neumann played an enthusiastic role in the development of thermonuclear weapons, ballistic missiles, the application of game theory to nuclear deterrence, and other known and unknown black arts. He was one of the few Manhattan Project scientists who was not sequestered at Los Alamos, appearing periodically, like a comet, in the course of his transcontinental rounds. Advocating a hard line against the Soviet Union and publicly favoring a preventive nuclear attack, his views on nuclear war were encapsulated in his 1950 motto “Not whether but when.” Nonetheless, he helped construct a policy of peace through the power of assured destruction that has avoided nuclear war for fifty years. Von Neumann’s statements must be viewed not only in historical perspective, but also in the context of his pioneering work in game theory, which demonstrated the possibility of stabilizing a dangerously unstable situation by a convincing bluff—if and only if there appears to be the determination to back it up.


pages: 137 words: 36,231

Information: A Very Short Introduction by Luciano Floridi

agricultural Revolution, Albert Einstein, bioinformatics, carbon footprint, Claude Shannon: information theory, conceptual framework, double helix, Douglas Engelbart, Douglas Engelbart, George Akerlof, Gordon Gekko, industrial robot, information asymmetry, intangible asset, Internet of things, invention of writing, John Nash: game theory, John von Neumann, Laplace demon, moral hazard, Nash equilibrium, Nelson Mandela, Norbert Wiener, Pareto efficiency, phenotype, Pierre-Simon Laplace, prisoner's dilemma, RAND corporation, RFID, Thomas Bayes, Turing machine, Vilfredo Pareto

Unlike the other three outcomes, the case in which both prisoners defect can also be described as a Nash equilibrium: it is the only outcome in which each player is doing the best he can, given the available information about the other player's actions. Nash equilibria are crucial features in game theory, as they represent situations in which no player's position can be improved by selecting any other available strategy while all the other players are also playing their best option and not changing their strategies. They are named after John Nash (born 1928), who, in 1994, shared the Nobel Prize in Economics with Reinhard Selten (born 1930) and John Harsanyi (1920-2000) for their foundational work on game theory. Complete information makes simultaneous games interesting. Without such a condition, the players would be unable to predict the effects of their actions on the other players' behaviour.

Indeed, information-theoretical approaches to economic topics have become so popular and pervasive that one may be forgiven for mistaking economics for a branch of information science. In the rest of this chapter, we will look at some essential ways in which economic information is used. For the sake of simplicity, and following current trends, the presentation will be framed in game-theoretic terms. But instead of presenting a standard analysis of types of games first, we will focus on the concepts of information and then see how they are used. Complete information Game theory is the formal study of strategic situations and interactions (games) among agents (players, not necessarily human), who are fully rational (they always maximize their payoffs, without any concern for the other players), aware of each other, and aware that their decisions are mutually dependent and affect the resulting payoffs. Generally speaking, a game is described by four elements: (a) its players, how many and who they are; (b) each player's strategies, what they may rationally decide to do given the known circumstances (a strategy is a complete plan of action specifying a feasible action for every move the player might have to make); (c) the resulting payoffs from each outcome, what they will gain by their moves; and (d) the sequence (timing or order) of the actual moves or states, if the game is sequential (see below), basically in what position the player is at a certain stage of the game.

Generally speaking, a game is described by four elements: (a) its players, how many and who they are; (b) each player's strategies, what they may rationally decide to do given the known circumstances (a strategy is a complete plan of action specifying a feasible action for every move the player might have to make); (c) the resulting payoffs from each outcome, what they will gain by their moves; and (d) the sequence (timing or order) of the actual moves or states, if the game is sequential (see below), basically in what position the player is at a certain stage of the game. One of game theory's main goals is to identify the sort of stable situations (equilibria) in which the game players have adopted strategies that they are unlikely to change, even if, from a sort of God's eye perspective, they may not be rationally optimal. There are many kinds of game and hence forms of equilibrium. One way of classifying them is by checking how much game-relevant information the players enjoy, that is, who has what kind of access to (a)-(d).


pages: 338 words: 106,936

The Physics of Wall Street: A Brief History of Predicting the Unpredictable by James Owen Weatherall

Albert Einstein, algorithmic trading, Antoine Gombaud: Chevalier de Méré, Asian financial crisis, bank run, beat the dealer, Benoit Mandelbrot, Black Swan, Black-Scholes formula, Bonfire of the Vanities, Bretton Woods, Brownian motion, business cycle, butterfly effect, buy and hold, capital asset pricing model, Carmen Reinhart, Claude Shannon: information theory, collateralized debt obligation, collective bargaining, dark matter, Edward Lorenz: Chaos theory, Edward Thorp, Emanuel Derman, Eugene Fama: efficient market hypothesis, financial innovation, fixed income, George Akerlof, Gerolamo Cardano, Henri Poincaré, invisible hand, Isaac Newton, iterative process, John Nash: game theory, Kenneth Rogoff, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, martingale, Myron Scholes, new economy, Paul Lévy, Paul Samuelson, prediction markets, probability theory / Blaise Pascal / Pierre de Fermat, quantitative trading / quantitative finance, random walk, Renaissance Technologies, risk-adjusted returns, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Coase, Sharpe ratio, short selling, Silicon Valley, South Sea Bubble, statistical arbitrage, statistical model, stochastic process, The Chicago School, The Myth of the Rational Market, tulip mania, Vilfredo Pareto, volatility smile

He made a list of the courses he would need to take, most of which were in a then-burgeoning field known as functional analysis, and discovered that if he took them all, he’d have enough for a PhD in mathematics, while his work on physics would have just begun. And so he switched to math. All the while, his ideas about the physics of roulette spun around in his mind. He was sure that with the right resources — a professional roulette wheel and some computer know-how — he could strike it rich. Soon after finishing his PhD, Thorp was awarded the prestigious C.L.E. Moore instructorship in mathematics at MIT — a position held a decade earlier by John Nash, the pioneering mathematician profiled by Sylvia Nasar in her book A Beautiful Mind. Thorp and his wife, Vivian, left Southern California and moved to Cambridge, Massachusetts. They spent only two years on the East Coast before moving back west, to New Mexico. But it was enough to set their lives on a different track: it was at MIT that Thorp met Claude Shannon. Shannon may be the only person in the twentieth century who can claim to have founded an entirely new science.

In The Cambridge History of Science, 275–305. New York: Cambridge University Press. Morley, Henry. 1854. The Life of Girolamo Cardano, of Milan, Physician. London: Chapman and Hall. Moynihan, Daniel P. 1996. Miles to Go: A Personal History of Social Policy. Cambridge, MA: Harvard University Press. Nasar, Sylvia. 1998. A Beautiful Mind: The Life of Mathematical Genius and Nobel Laureate John Nash. New York: Touchstone. Ndiaye, Pap A. 2007. Nylon and Bombs. Baltimore, MD: Johns Hopkins University Press. Niederhoffer, Victor. 1998. The Education of a Speculator. Hoboken, NJ: John Wiley and Sons. Niederhoffer, Victor, and M.F.M. Osborne. 1966. “Market Making and Reversals on the Stock Exchange.” Journal of the American Statistical Association 61 (316): 897–916. Nocera, Joe. 2007.

Card counting is a process by which you gain information about the deck of cards — you learn how the composition of the deck has changed with each hand. This is just what you need to calculate your advantage, as Kelly proposed. Information flows and your money grows. As Thorp and Kimmel made their preparations for Reno, Shannon and Thorp were collaborating on Thorp’s roulette plan. When he heard Thorp’s ideas, Shannon was mesmerized, in large part because Thorp’s roulette idea combined game theory with Shannon’s real passion: machines. At the heart of the idea was a wearable computer that would perform the necessary calculations for the player. They began testing ideas for how the actual gambling would work, assuming they could make sufficient progress on the prediction algorithm. They agreed that it would take more than one person for it to go smoothly, because one person couldn’t focus sufficiently on the wheel to input the necessary data and still be prepared to bet before the ball slowed down and the croupier (roulette’s equivalent of a dealer) announced that betting was closed.


pages: 545 words: 137,789

How Markets Fail: The Logic of Economic Calamities by John Cassidy

"Robert Solow", Albert Einstein, Andrei Shleifer, anti-communist, asset allocation, asset-backed security, availability heuristic, bank run, banking crisis, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, Black-Scholes formula, Blythe Masters, Bretton Woods, British Empire, business cycle, capital asset pricing model, centralized clearinghouse, collateralized debt obligation, Columbine, conceptual framework, Corn Laws, corporate raider, correlation coefficient, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, Daniel Kahneman / Amos Tversky, debt deflation, different worldview, diversification, Elliott wave, Eugene Fama: efficient market hypothesis, financial deregulation, financial innovation, Financial Instability Hypothesis, financial intermediation, full employment, George Akerlof, global supply chain, Gunnar Myrdal, Haight Ashbury, hiring and firing, Hyman Minsky, income per capita, incomplete markets, index fund, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), invisible hand, John Nash: game theory, John von Neumann, Joseph Schumpeter, Kenneth Arrow, Kickstarter, laissez-faire capitalism, Landlord’s Game, liquidity trap, London Interbank Offered Rate, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, margin call, market bubble, market clearing, mental accounting, Mikhail Gorbachev, money market fund, Mont Pelerin Society, moral hazard, mortgage debt, Myron Scholes, Naomi Klein, negative equity, Network effects, Nick Leeson, Northern Rock, paradox of thrift, Pareto efficiency, Paul Samuelson, Ponzi scheme, price discrimination, price stability, principal–agent problem, profit maximization, quantitative trading / quantitative finance, race to the bottom, Ralph Nader, RAND corporation, random walk, Renaissance Technologies, rent control, Richard Thaler, risk tolerance, risk-adjusted returns, road to serfdom, Robert Shiller, Robert Shiller, Ronald Coase, Ronald Reagan, shareholder value, short selling, Silicon Valley, South Sea Bubble, sovereign wealth fund, statistical model, technology bubble, The Chicago School, The Great Moderation, The Market for Lemons, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, unorthodox policies, value at risk, Vanguard fund, Vilfredo Pareto, wealth creators, zero-sum game

The article was long and involved. Unlike Wald’s work from 1934, it didn’t use any simplifying assumptions about the factors that influence demand, and unlike von Neumann’s 1937 paper, it treated both consumers and firms extensively. Mathematically sophisticated, it eschewed calculus, which was rapidly becoming old hat, and instead made extensive use of convex sets, game theory, and fixed-point theorems—borrowing an application of the last from John Nash, the Princeton mathematician and game theorist. The Arrow-Debreu paper was nobody’s idea of bedtime reading, but when their colleagues had made their way through it, they were agreed: Walras’s problem had finally been solved, and the case for competitive markets had been placed on a sound analytical foundation, or so it seemed. More than half a century later, the argument is still resting on the same support.

In games of that nature, the players compete against one another, and one player’s winnings are another player’s losses. But many types of economic activity, such as international trade and investing in the stock market, involve the possibility of cooperation and mutual gains: they are positive-sum games. During the late 1940s, some progress was made in tackling this broader category of problems when John Nash, a Princeton mathematician, introduced a general method for solving non-zero-sum games, but much remained unclear. Merrill Flood and Melvin Dresher were two mathematicians working at the RAND Corporation, which the Pentagon had founded in the aftermath of World War II to engage in scientific research “for the public welfare and security of the United States of America.” Much of the work undertaken at RAND had military implications, but it was also an important center of operations research and other applications of mathematics.

THE PRISONER’S DILEMMA AND RATIONAL IRRATIONALITY 143 Flood’s babysitting experiment: See William Poundstone, The Prisoner’s Dilemma: John Von Neumann, Game Theory, and the Puzzle of the Bomb (New York: Doubleday, 1992), 103. 143 Non-cooperative pair experiment: Ibid., 106–107. 145 “Both Flood and Dresher . . .”: Ibid., 122. 147 90 percent of the players choose: Ken Binmore, Game Theory: A Very Short Introduction (New York: Oxford University Press, 2007), 21. 149 “Adding together the component . . .”: Garrett Hardin, “The Tragedy of the Commons,” Science 162 (1968): 1244. 150 “Game theorists get . . .”: Binmore, Game Theory, 67. 12. HIDDEN INFORMATION AND THE MARKET FOR LEMONS 151 “I belonged to . . .”: From George Akerlof’s Nobel autobiography, available at http://nobelprize.org/nobel_prizes/economics/laureates/2001/akerlof-autobio.html. 152 “a major reason as to why . . .”: George Akerlof, “Writing ‘The Market for Lemons’: A Personal and Interpretive Essay,” available at http://nobelprize.org/nobel_prizes/economics/articles/akerlof/index.html. 153 “[M]ost cars traded . . .”: George Akerlof, “The Market for ‘Lemons’: Quality Uncertainty and the Market Mechanism,” Quarterly Journal of Economics 84 (1970): 489. 154 “was potentially an issue . . .”: Akerlof, “Writing ‘The Market for Lemons.’ ” 155 “marginally attached”: Bureau of Labor Statistics, Issues in Labor Statistics, Summary 90–04 (April 2009): 1. 156 “it is quite possible . . .”: Akerlof, “The Market for ‘Lemons,’ ” 494. 157 2006 health care spending: “National Health Spending in 2006: A Year of Change for Prescription Drugs,” Health Affairs 27, no. 1 (2008): 14. 158 “The most obvious . . .”: Kenneth J.


pages: 251 words: 44,888

The Words You Should Know to Sound Smart: 1200 Essential Words Every Sophisticated Person Should Be Able to Use by Bobbi Bly

Albert Einstein, Alistair Cooke, Anton Chekhov, British Empire, Columbine, Donald Trump, George Santayana, haute couture, Honoré de Balzac, Joan Didion, John Nash: game theory, Network effects, placebo effect, Ralph Waldo Emerson, school vouchers, Stephen Hawking, Steve Jobs

frisson (FREE-son), noun A sudden strong feeling of excitement, conflict, or danger. “Pregnant women! They had that weird FRISSON, an aura of magic that combined awkwardly with an earthy sense of duty.” – Ruth Morgan, American novelist fruition (froo-ISH-un), noun The completion of a task; the achievement of a goal as the result of significant and persistent effort. John Nash, a mathematician whose life was featured in “A Beautiful Mind,” received the Nobel Prize for the FRUITION of his work in game theory decades after he completed it. fulsome (FULL-sum), adjective Describes words or actions that praise or flatter someone to an excessive degree. Katie’s introduction of the keynote speaker was so FULSOME that he led his speech with a few self-effacing remarks. fungible (FUHN-jih-bull), adjective Freely exchangeable for another of like nature; interchangeable.


pages: 254 words: 61,387

This Could Be Our Future: A Manifesto for a More Generous World by Yancey Strickler

basic income, big-box store, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, cognitive dissonance, corporate governance, Daniel Kahneman / Amos Tversky, David Graeber, Donald Trump, Doomsday Clock, effective altruism, Elon Musk, financial independence, gender pay gap, global supply chain, housing crisis, Ignaz Semmelweis: hand washing, invention of the printing press, invisible hand, Jeff Bezos, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Nash: game theory, Joi Ito, Joseph Schumpeter, Kickstarter, Louis Pasteur, Mark Zuckerberg, medical bankruptcy, new economy, Oculus Rift, off grid, offshore financial centre, Ralph Nader, RAND corporation, Richard Thaler, Ronald Reagan, self-driving car, shareholder value, Silicon Valley, Simon Kuznets, Snapchat, Social Responsibility of Business Is to Increase Its Profits, stem cell, Steve Jobs, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, Travis Kalanick, universal basic income, white flight

To study the situation, the researchers turned to a then-new field called game theory. Game theory uses mathematical models to determine the optimal, rational strategies in games and other strategic conflicts. When applied to the nuclear standoff with the Soviet Union, game theory allowed the scientists to consider different approaches the United States might take, how the USSR might respond, and where things might go from there. This greatly expanded the decision makers’ awareness of the potential outcomes of whatever strategy they considered. The RAND scientists created a variety of scenarios to explore different kinds of conflicts. Many of these scenarios were interactive games that people would play. Arguably the most famous example of a game theory scenario, called Prisoner’s Dilemma, was created at RAND in 1950.

Many of them chose to stay loyal to their partners. Their relationships were what mattered to them. The secretaries achieved the ideal outcome of the game. According to the model of rationality set by game theory, the secretaries weren’t playing correctly. Pursuing your immediate self-interest was the rational thing to do. * * * ■ ■ ■ ■ The RAND Corporation published The Compleat Strategyst with the goal of expanding the application of game theory in day-to-day life. “We believe it possible that Game Theory, as it develops—or something like it—may become an important concept and force in many phases of life,” author J. D. Williams wrote. They were right. Game theory became a tool for a new kind of “hyperrational” way of thinking. A view that, among other things, teaches the rationality of maximizing one’s self-interest.

I wanted to make the case that nonfinancial value was just as rational as financial value. Had anyone made this case before? And then one day I found something. While reading a fascinating book called Age of Fracture by Daniel Rodgers, I came across mention of a movement called communitarianism, where a more expansive set of values was embraced. In fact, one of the core game theorists at the RAND Corporation (John Nash, subject of the biography and film A Beautiful Mind) moved to a communitarian community in the 1970s. Intrigued, I continued to dig into communitarianism until I came across a book by Michael Walzer. Walzer is a professor emeritus of social science at Princeton University’s Institute for Advanced Study. He wrote Spheres of Justice: A Defense of Pluralism and Equality in 1983. It was in this little-known book that I discovered a different notion of value.


pages: 295 words: 66,824

A Mathematician Plays the Stock Market by John Allen Paulos

Benoit Mandelbrot, Black-Scholes formula, Brownian motion, business climate, business cycle, butter production in bangladesh, butterfly effect, capital asset pricing model, correlation coefficient, correlation does not imply causation, Daniel Kahneman / Amos Tversky, diversified portfolio, dogs of the Dow, Donald Trump, double entry bookkeeping, Elliott wave, endowment effect, Erdős number, Eugene Fama: efficient market hypothesis, four colour theorem, George Gilder, global village, greed is good, index fund, intangible asset, invisible hand, Isaac Newton, John Nash: game theory, Long Term Capital Management, loss aversion, Louis Bachelier, mandelbrot fractal, margin call, mental accounting, Myron Scholes, Nash equilibrium, Network effects, passive investing, Paul Erdős, Paul Samuelson, Ponzi scheme, price anchoring, Ralph Nelson Elliott, random walk, Richard Thaler, Robert Shiller, Robert Shiller, short selling, six sigma, Stephen Hawking, stocks for the long run, survivorship bias, transaction costs, ultimatum game, Vanguard fund, Yogi Berra

Imagine the Andersen accountants muttering anxiously that there weren’t enough leading “1s” on the documents they were feeding into the shredders. A 1-derful fantasy! The Numbers Man—A Screen Treatment An astonishing amount of attention has been paid recently to fictional and narrative treatments of mathematical topics. The movies Good Will Hunting, Pi, and The Croupier come to mind; so do plays such as Copenhagen, Arcadia, and The Proof, the two biographies of Paul Erdos, A Beautiful Mind, the biography of John Nash (with its accompanying Academy Award-winning movie), TV specials on Fermat’s Last Theorem, and other mathematical topics, as well as countless books on popular mathematics and mathematicians. The plays and movies, in particular, prompted me to expand the idea in the stock-newsletter scam discussed above (I changed the focus, however, from stocks to sports) into a sort of abbreviated screen treatment that highlights the relevant mathematics a bit more than has been the case in the productions just cited.

It requires faster machines, better data, improved models, and the smarter use of mathematical tools, from conventional statistics to neural nets (computerized learning networks, the connections between the various nodes of which are strengthened or weakened over a period of training). If this is possible for anyone or any group to achieve, it’s not likely to remain so for long. Game Theory and Supernatural Investor/Psychologists But what if, contrary to fact, there were an entity possessing sufficient complexity and speed that it was able with reasonably high probability to predict the market and the behavior of individuals within it? The mere existence of such an entity leads to Newcombe’s paradox, a puzzle that calls into question basic principles of game theory. My particular variation of Newcombe’s paradox involves the World Class Options Market Maker (WCOMM), which (who?) claims to have the power to predict with some accuracy which of two alternatives a person will choose.

Chapter 8 - Connectedness and Chaotic Price Movements Insider Trading and Subterranean Information Processing Trading Strategies, Whim, and Ant Behavior Chaos and Unpredictability Extreme Price Movements, Power Laws, and the Web Economic Disparities and Media Disproportions Chapter 9 - From Paradox to Complexity The Paradoxical Efficient Market Hypothesis The Prisoner’s Dilemma and the Market Pushing the Complexity Horizon Game Theory and Supernatural Investor/Psychologists Absurd Emails and the WorldCom Denouement Bibliography Index Copyright Page Also by John Allen Paulos Mathematics and Humor (1980) I Think Therefore I Laugh (1985) Innumeracy: Mathematical Illiteracy and its Consequences (1988) Beyond Numeracy: Ruminations of a Numbers Man (1991) A Mathematician Reads the Newspaper (1995) Once Upon a Number: The Hidden Mathematical Logic of Stories (1998) To my father, who never played the market and knew little about probability, yet understood one of the prime lessons of both.


pages: 262 words: 65,959

The Simpsons and Their Mathematical Secrets by Simon Singh

Albert Einstein, Andrew Wiles, Benoit Mandelbrot, cognitive dissonance, Donald Knuth, Erdős number, Georg Cantor, Grace Hopper, Isaac Newton, John Nash: game theory, Kickstarter, mandelbrot fractal, Menlo Park, Norbert Wiener, Norman Mailer, P = NP, Paul Erdős, probability theory / Blaise Pascal / Pierre de Fermat, Richard Feynman, Rubik’s Cube, Schrödinger's Cat, Simon Singh, Stephen Hawking, Wolfskehl Prize, women in the workforce

Although we have not yet discussed the Erdős-Bacon numbers for the rest of the writing team behind The Simpsons, I can confirm that none of them can beat Westbrook’s score. In other words, out of the entire gang of Tinseltown nerds, Westbrook is overall the tinseliest and the nerdiest.8 I first became aware of Erdős-Bacon numbers thanks to Dave Bayer, a mathematician at Colombia University. He was a consultant on the film A Beautiful Mind, based on Sylvia Nasar’s acclaimed biography of the mathematician John Nash, who had won the Nobel Prize in Economic Sciences in 1994. Bayer’s responsibilities included checking the equations that appeared on screen and acting as Russell Crowe’s hand double in the blackboard scenes. Bayer was also given a minor role toward the end of the film, when the Princeton mathematics professors offer their pens to Nash to acknowledge his great discoveries. Bayer proudly explained: “In my scene, known as the Pen Ceremony, I say, ‘A privilege, professor.’

Joel Sokol at the Georgia Institute of Technology gives a lecture titled “Making Decisions Against an Opponent: An Application of Mathematical Optimization,” which includes slides describing games of rock-paper-scissors played by characters in The Simpsons. The lecture focuses on game theory, an area of mathematics concerned with modeling how participants behave in situations of conflict and cooperation. Game theory can offer insights into everything from dominoes to warfare, from animal altruism to trade union negotiations. Similarly, Dirk Mateer, an economist at Pennsylvania State University with a strong interest in mathematics, also makes use of The Simpsons and scenes involving rock-paper-scissors when he teaches game theory to his students. Rock-paper-scissors (RPS) seems like a trivial game, so you might be surprised that it is of any mathematical interest. However, in the hands of a game theorist, RPS becomes a complex battle between two competitors trying to outwit each other.

However, all these philosophers, psychologists, theologians, and politicians have missed the primary subtext of the world’s favorite TV series. The truth is that many of the writers of The Simpsons are deeply in love with numbers, and their ultimate desire is to drip-feed morsels of mathematics into the subconscious minds of viewers. In other words, for more than two decades we have been tricked into watching an animated introduction to everything from calculus to geometry, from π to game theory, and from infinitesimals to infinity. “Homer3,” the third segment in the three-part episode “Treehouse of Horror VI” (1995) demonstrates the level of mathematics that appears in The Simpsons. In one sequence alone, there is a tribute to history’s most elegant equation, a joke that only works if you know about Fermat’s last theorem, and a reference to a $1 million mathematics problem. All of this is embedded within a narrative that explores the complexities of higher-dimensional geometry.


pages: 252 words: 73,131

The Inner Lives of Markets: How People Shape Them—And They Shape Us by Tim Sullivan

"Robert Solow", Airbnb, airport security, Al Roth, Alvin Roth, Andrei Shleifer, attribution theory, autonomous vehicles, barriers to entry, Brownian motion, business cycle, buy and hold, centralized clearinghouse, Chuck Templeton: OpenTable:, clean water, conceptual framework, constrained optimization, continuous double auction, creative destruction, deferred acceptance, Donald Trump, Edward Glaeser, experimental subject, first-price auction, framing effect, frictionless, fundamental attribution error, George Akerlof, Goldman Sachs: Vampire Squid, Gunnar Myrdal, helicopter parent, information asymmetry, Internet of things, invisible hand, Isaac Newton, iterative process, Jean Tirole, Jeff Bezos, Johann Wolfgang von Goethe, John Nash: game theory, John von Neumann, Joseph Schumpeter, Kenneth Arrow, late fees, linear programming, Lyft, market clearing, market design, market friction, medical residency, multi-sided market, mutually assured destruction, Nash equilibrium, Occupy movement, Pareto efficiency, Paul Samuelson, Peter Thiel, pets.com, pez dispenser, pre–internet, price mechanism, price stability, prisoner's dilemma, profit motive, proxy bid, RAND corporation, ride hailing / ride sharing, Robert Shiller, Robert Shiller, Ronald Coase, school choice, school vouchers, sealed-bid auction, second-price auction, second-price sealed-bid, sharing economy, Silicon Valley, spectrum auction, Steve Jobs, Tacoma Narrows Bridge, technoutopianism, telemarketer, The Market for Lemons, The Wisdom of Crowds, Thomas Malthus, Thorstein Veblen, trade route, transaction costs, two-sided market, uber lyft, uranium enrichment, Vickrey auction, Vilfredo Pareto, winner-take-all economy

When Arrow spoke with one of his mentors at Columbia, the great statistician Abraham Wald, about this question of proving the existence of equilibrium, he was told “it is a very difficult issue”—as in, “too difficult for the likes of you.” That challenge helped spur Arrow, who went ahead and proved it anyway. The year 1951 had seen a major technical advance that made proof of existence far easier than Wald might have realized. John Nash, the game theorist made famous by the book and movie A Beautiful Mind, had borrowed the fixed-point theorem of Japanese mathematician Shizuo Kakutani to prove the existence of Nash equilibrium in game theory. In Arrow’s retelling, at that point it was obvious how to go about proving the existence of competitive equilibrium, and it was a race among himself, French economist Debreu, and several others to see who could do it first and do it best. As Arrow recalls, he summarized his first attempt at proving the existence theorem in a working paper just before heading to Europe to give some lectures.

The foundation’s founding motto was “Science is Measurement.”11 The second, the RAND Corporation, first established as a joint project by the Douglas Aircraft Company and the US Department of War in 1945, used game theory to analyze the United States’s geopolitical position relative to the Soviet Union. Game theory—a mathematical approach to analyzing strategic choices—emerged from the work of Princeton mathematician John von Neumann in the 1930s, who collaborated with his economist colleague Oskar Morgenstern to write Theory of Games and Economic Behavior (published in 1944), which launched the field. Their book provided an analytical framework for figuring out, say, what Pepsi should do if Coke lowers its prices. That depends on how Pepsi’s CEO thinks Coke will respond, which in turn depends on what Coke’s CEO expects that Pepsi’s response to their price reduction will be. And so on. Game theory was a way of cutting through the infinite regression of “what he thinks I think he thinks . . .”

Game theory was a way of cutting through the infinite regression of “what he thinks I think he thinks . . .” Although technical, some of von Neumann and Morgenstern’s ideas eventually filtered into the mainstream, and so resonated with the public imagination that the two researchers found themselves on the front page of the New York Times in 1946 under the headline, “Mathematical Theory of Poker Is Applied to Business Problems.”12 Game theory, though, was about much more than just business. Most famously, perhaps, RAND economists and mathematicians developed the doctrine of nuclear deterrence by mutually assured destruction (MAD) under the guidance of then defense secretary Robert McNamara (himself an economist by training). Von Neumann and Morgenstern’s Theory of Games and Economic Behavior is, in concentrated form, the story of how the new mathematical science of economics could operate and change the way the world works in arenas small (poker) and earth shattering (thermonuclear war).


pages: 288 words: 81,253

Thinking in Bets by Annie Duke

banking crisis, Bernie Madoff, Cass Sunstein, cognitive bias, cognitive dissonance, Daniel Kahneman / Amos Tversky, delayed gratification, Donald Trump, en.wikipedia.org, endowment effect, Estimating the Reproducibility of Psychological Science, Filter Bubble, hindsight bias, Jean Tirole, John Nash: game theory, John von Neumann, loss aversion, market design, mutually assured destruction, Nate Silver, p-value, phenotype, prediction markets, Richard Feynman, ride hailing / ride sharing, Stanford marshmallow experiment, Stephen Hawking, Steven Pinker, the scientific method, The Signal and the Noise by Nate Silver, urban planning, Walter Mischel, Yogi Berra, zero-sum game

Initial reviews in the most prestigious academic journals heaped it with praise, like “one of the major scientific achievements of the first half of the twentieth century” and “ten more such books and the progress of economics is assured.” Game theory revolutionized economics, evidenced by at least eleven economics Nobel laureates connected with game theory and its decision-making implications, including John Nash (a student of von Neumann’s), whose life story was chronicled in the Oscar-winning film A Beautiful Mind. Game theory has broad applications outside economics, informing the behavioral sciences (including psychology and sociology) as well as political science, biomedical research, business, and numerous other fields. Game theory was succinctly defined by economist Roger Myerson (one of the game-theory Nobel laureates) as “the study of mathematical models of conflict and cooperation between intelligent rational decision-makers.” Game theory is the modern basis for the study of the bulk of our decision-making, addressing the challenges of changing conditions, hidden information, chance, and multiple people involved in the decisions.

The influence of John von Neumann on game theory, and of game theory on modern economics, is unquestioned. At least eleven Nobel laureates in economics have been cited for their work connected with or influenced by game theory. NobelPrize.org has cited the following eleven winners of the Prize in Economic Sciences (formally called “The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel”), by year, field, and contribution: (1) John C. Harsanyi, (2) John F. Nash Jr., and (3) Reinhard Selten (1994, game theory, “for their pioneering analysis of equilibria in the theory of non-cooperative games”); (4) Robert J. Aumann and (5) Thomas C. Schelling (2005, game theory, “for having enhanced our understanding of conflict and cooperation through game theory analysis”); (6) Leonid Hurwicz, (7) Eric S. Maskin, and (8) Roger B. Myerson (2007, microeconomics, “for having laid the foundations of mechanism design theory”); (9) Alvin E.

Game theory is the modern basis for the study of the bulk of our decision-making, addressing the challenges of changing conditions, hidden information, chance, and multiple people involved in the decisions. Sound familiar? Fortunately, you don’t need to know any more than this about game theory to understand its relevance. And the important thing for this book is that John von Neumann modeled game theory on a stripped-down version of poker. Poker vs. chess In The Ascent of Man, scientist Jacob Bronowski recounted how von Neumann described game theory during a London taxi ride. Bronowski was a chess enthusiast and asked him to clarify. “You mean, the theory of games like chess?” Bronowski quoted von Neumann’s response: “‘No, no,’ he said. ‘Chess is not a game. Chess is a well-defined form of computation. You may not be able to work out the answers, but in theory there must be a solution, a right procedure in any position.


pages: 272 words: 83,798

A Little History of Economics by Niall Kishtainy

"Robert Solow", Alvin Roth, British Empire, Capital in the Twenty-First Century by Thomas Piketty, car-free, central bank independence, clean water, Corn Laws, creative destruction, credit crunch, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, Eugene Fama: efficient market hypothesis, first-price auction, floating exchange rates, follow your passion, full employment, George Akerlof, greed is good, Hyman Minsky, inflation targeting, invisible hand, John Nash: game theory, John von Neumann, Joseph Schumpeter, Kenneth Arrow, loss aversion, market clearing, market design, means of production, moral hazard, Nash equilibrium, new economy, Occupy movement, Pareto efficiency, Paul Samuelson, prisoner's dilemma, RAND corporation, rent-seeking, Richard Thaler, rising living standards, road to serfdom, Robert Shiller, Robert Shiller, Ronald Reagan, sealed-bid auction, second-price auction, The Chicago School, The Great Moderation, The Market for Lemons, The Wealth of Nations by Adam Smith, Thomas Malthus, Thorstein Veblen, trade route, Vickrey auction, Vilfredo Pareto, washing machines reduced drudgery, wealth creators, Winter of Discontent

So there was a need for a method that worked for other kinds of games, including ones where the players wouldn’t necessarily stick to any promises they made to each other. In 1950 a mathematician named John Nash (1928–2015) came up with a solution. Nash thought of his idea when he was still a student at Princeton University. He decided to pay a visit to von Neumann, who was then a Princeton professor, to tell him about it. Even though von Neumann was by then very famous, it didn’t deter Nash. (Before that, he’d popped in to see Einstein to discuss some new ideas he’d had about the expansion of the universe.) The great von Neumann sent Nash away, telling him that his idea was trivial. In fact Nash’s idea became the most important in game theory, still used all the time today. He said that the outcome of a game – its ‘equilibrium’ – is that in which each player does the best for himself given what the other player does.

Both end up with huge stocks of missiles aimed at their enemy. The arms race is an example of ‘game theory’, a field of mathematics and economics that emerged in the 1940s and 1950s. Game theory looks at how countries, firms and people behave in situations in which what one side does affects outcomes for the other. When your enemy buys missiles it puts you at a disadvantage and makes your country less safe; when you buy missiles you do the same to your enemy. Each side needs to decide what to do, taking into account what their enemy might do. Game theorists call it ‘strategic interaction’: we affect each other (we ‘interact’) and so we decide what to do in the light of what our enemy does (we’re ‘strategic’). Game theory is the study of strategic interactions that are found everywhere, from simple games like rock-paper-scissors to the search for profit by businesses and the wars fought between nations.

Strangelove was a 1964 film that poked fun at the rivalry, and as well as being a gripping story, it’s an excellent introduction to the era of game theory and to some of the basic ideas. During the Cold War, the American military paid for research into areas helpful to national security and game theory was one of them. Many game theorists worked for the RAND (‘research and development’) Corporation, a military research organisation. In the film, Dr Strangelove is the American president’s director of weapons research, an eccentric genius with dark glasses and a funny accent who advises on military tactics. He’s said to have been inspired by a real genius, the Hungarian-born mathematician John von Neumann (1903–57), one of the founders of game theory who worked for RAND and became President Eisenhower’s adviser on defence strategy. Von Neumann was so clever that at the age of eight he could divide eight-digit numbers in his head.


pages: 280 words: 85,091

The Wisdom of Psychopaths: What Saints, Spies, and Serial Killers Can Teach Us About Success by Kevin Dutton

Asperger Syndrome, Bernie Madoff, business climate, corporate governance, corporate social responsibility, delayed gratification, epigenetics, Fellow of the Royal Society, G4S, impulse control, iterative process, John Nash: game theory, meta analysis, meta-analysis, Nicholas Carr, Norman Mailer, place-making, RAND corporation, Ronald Reagan, Steve Jobs, Steven Pinker, theory of mind, ultimatum game

Profoundly autistic, John and Michael, then twenty-six, were living in an institution. When a box of matches spilled onto the floor, both of them simultaneously called out “111.” As Sacks gathered up the matches, he started counting … On a similar note, the well-worn stereotype of the brilliant “tortured artist” is also not without foundation. The painter Vincent van Gogh, the dancer Vaslav Nijinsky, and the father of “game theory” (of which more later) John Nash were all psychotic. Coincidence? Not according to Szabolcs Kéri, a researcher at Semmelweis University in Budapest, who appears to have uncovered a genetic polymorphism associated with both schizophrenia and creativity. Kéri has found that people with two copies of a particular single-letter DNA variation in a gene called neuregulin 1, a variation that has been previously linked to psychosis—as well as poor memory and sensitivity to criticism—tend to score significantly higher on measures of creativity compared with individuals who have one or no copy of the variation.

So which one are you: psychopath, saint, or somewhere in between? The chances are it’s going to be the latter—for which, it turns out, there are sound biological reasons. To Plea or Not to Plea We’ve already seen game theory in action earlier in this chapter. A branch of applied mathematics devoted to the study of strategic situations, to the selection of optimal behavioral strategies in circumstances in which the costs and benefits of a particular choice or decision are not set in stone but are, in contrast, variable, game theory presents scenarios that are intrinsically dynamic. Unsurprisingly perhaps, given game theory’s inherent emphasis on the relationship between individual agency and the wider social group, it’s not uncommon to find rich incrustations of this semiprecious mathematical outcrop embedded within branches of natural selection—within models and theories of how various behaviors or life strategies might have evolved.

To answer this question, Meloy goes back in time to prehistory and the shadowy, spectral dictates of human evolution. There are a number of theories about how psychopathy might first have developed, and we’ll be looking at those a little later on. But an overarching question in the grand etiological scheme of things is from which ontological perspective the condition should actually be viewed: from a clinical standpoint, as a disorder of personality? Or from a game theory standpoint, as a legitimate biological gambit—a life history strategy conferring significant reproductive advantages in the primeval ancestral environment? Kent Bailey, emeritus professor in clinical psychology at Virginia Commonwealth University, argues in favor of the latter, and advances the theory that violent competition within and between proximal ancestral groups was the primary evolutionary precursor of psychopathy (or, as he puts it, the mind-set of the “warrior hawk”).


pages: 302 words: 83,116

SuperFreakonomics by Steven D. Levitt, Stephen J. Dubner

agricultural Revolution, airport security, Andrei Shleifer, Atul Gawande, barriers to entry, Bernie Madoff, Boris Johnson, call centre, clean water, cognitive bias, collateralized debt obligation, creative destruction, credit crunch, Daniel Kahneman / Amos Tversky, deliberate practice, Did the Death of Australian Inheritance Taxes Affect Deaths, disintermediation, endowment effect, experimental economics, food miles, indoor plumbing, Intergovernmental Panel on Climate Change (IPCC), John Nash: game theory, Joseph Schumpeter, Joshua Gans and Andrew Leigh, longitudinal study, loss aversion, Louis Pasteur, market design, microcredit, Milgram experiment, oil shale / tar sands, patent troll, presumed consent, price discrimination, principal–agent problem, profit motive, randomized controlled trial, Richard Feynman, Richard Thaler, selection bias, South China Sea, Stanford prison experiment, Stephen Hawking, The Wealth of Nations by Adam Smith, too big to fail, trickle-down economics, ultimatum game, urban planning, William Langewiesche, women in the workforce, young professional

Most of the problems they traditionally worry about—the effect of tax increases, for instance, or the causes of inflation—are difficult to capture there. But if the lab could unravel the scientific mysteries of the universe, surely it could help figure out something as benign as altruism. These new experiments typically took the form of a game, run by college professors and played by their students. This path had been paved by the beautiful mind of John Nash and other economists who, in the 1950s, experimented broadly with the Prisoner’s Dilemma, a game-theory problem that came to be seen as a classic test of strategic cooperation. (It was invented to glean insights about the nuclear standoff between the United States and the Soviet Union.) By the early 1980s, the Prisoner’s Dilemma had inspired a lab game called Ultimatum, which works as follows. Two players, who remain anonymous to each other, have a onetime chance to split a sum of money.

List, “What Do Laboratory Experiments Measuring Social Preferences Tell Us About the Real World,” Journal of Economic Perspectives 21, no. 2 (2007). See also: Daniel Kahneman, Jack L. Knetsch, and Richard Thaler, “Fairness as a Constraint on Profit Seeking: Entitlements in the Market,” American Economic Review 76, no. 4 (September 1986); Robert Forsythe, Joel L. Horowitz, N. E. Savin, and Martin Sef-ton, “Fairness in Simple Bargaining Experiments,” Games and Economic Behavior 6, no. 3 (May 1994); Colin F. Camerer, Behavioral Game Theory (Princeton University Press, 2003); and John A. List, “Dictator Game Giving Is an Experimental Artifact,” working paper, 2005. ORGAN TRANSPLANTS: The first successful long-term kidney transplant was performed at the Peter Bent Brigham Hospital in Boston by Joseph Murray in December 1954, as related in Nicholas Tilney, Transplant: From Myth to Reality (Yale University Press, 2003). / 111 “Donorcyclists”: see Stacy Dickert-Conlin, Todd Elder, and Brian Moore, “Donorcycles: Do Motorcycle Helmet Laws Reduce Organ Donations?”


pages: 323 words: 95,939

Present Shock: When Everything Happens Now by Douglas Rushkoff

algorithmic trading, Andrew Keen, bank run, Benoit Mandelbrot, big-box store, Black Swan, British Empire, Buckminster Fuller, business cycle, cashless society, citizen journalism, clockwork universe, cognitive dissonance, Credit Default Swap, crowdsourcing, Danny Hillis, disintermediation, Donald Trump, double helix, East Village, Elliott wave, European colonialism, Extropian, facts on the ground, Flash crash, game design, global pandemic, global supply chain, global village, Howard Rheingold, hypertext link, Inbox Zero, invention of agriculture, invention of hypertext, invisible hand, iterative process, John Nash: game theory, Kevin Kelly, laissez-faire capitalism, lateral thinking, Law of Accelerating Returns, loss aversion, mandelbrot fractal, Marshall McLuhan, Merlin Mann, Milgram experiment, mutually assured destruction, negative equity, Network effects, New Urbanism, Nicholas Carr, Norbert Wiener, Occupy movement, passive investing, pattern recognition, peak oil, price mechanism, prisoner's dilemma, Ralph Nelson Elliott, RAND corporation, Ray Kurzweil, recommendation engine, selective serotonin reuptake inhibitor (SSRI), Silicon Valley, Skype, social graph, South Sea Bubble, Steve Jobs, Steve Wozniak, Steven Pinker, Stewart Brand, supply-chain management, the medium is the message, The Wisdom of Crowds, theory of mind, Turing test, upwardly mobile, Whole Earth Catalog, WikiLeaks, Y2K, zero-sum game

Even if there were millions of possible actors, actions, and connections, there were only two real superpowers—the Soviet Union and the United States. Military leaders figured that game theory, based on the mathematics of poker, should be able to model this activity and give us simple enough rules for engagement. And so the RAND Corporation was hired to conduct experiments (like the Prisoner’s Dilemma, which we looked at earlier), determine probable outcomes, and then program computers to respond appropriately in any number of individual circumstances. Led by the as yet undiagnosed paranoid schizophrenic John Nash (the mathematician portrayed in the movie A Beautiful Mind), they adopted a principle called MAD, or mutually assured destruction, which held that if the use of any nuclear device could effectively guarantee the complete and utter annihilation of both sides in the conflict, then neither side would opt to use them.

While this didn’t stop the superpowers from fighting smaller proxy wars around the world, it did serve as a deterrent to direct conflict. Encouraged by this success, Nash applied his game theory to all forms of human interaction. He won a Nobel Prize for showing that a system driven by suspicion and self-interest could reach a state of equilibrium in which everyone’s needs were met. “It is understood not to be a cooperative ideal,” he later admitted, but—at least at the time—neither he nor RAND thought human beings to be cooperative creatures. In fact, if the people in Nash’s equations attempted to cooperate, the results became much more dangerous, messy, and unpredictable. Altruism was simply too blurry. Good planning required predictable behaviors, and the assumption of short-term self-interest certainly makes things easy to see coming. A few decades of game theory and analysis since then have revealed the obvious flaws in Nash’s and RAND’s thinking.

A few decades of game theory and analysis since then have revealed the obvious flaws in Nash’s and RAND’s thinking. As Hungarian mathematician and logician László Méro explains it in his rethink of game theory, Moral Calculations,9 the competitive assumptions in game theory have not been proved by consistent results in real-world examples. In study after study, people, animals, and even bacteria are just as likely to cooperate as they are to compete. The reason real human behavior differs from that of the theoretically self-interested prisoners is that the latter are prisoners to begin with. An incarcerated person is the most literal example of one living within a closed environment. These are individuals without access to information and incapable of exercising basic freedoms. All feedback and iteration are removed, other than that between the prisoner and his keepers.


pages: 417 words: 97,577

The Myth of Capitalism: Monopolies and the Death of Competition by Jonathan Tepper

Affordable Care Act / Obamacare, air freight, Airbnb, airline deregulation, bank run, barriers to entry, Berlin Wall, Bernie Sanders, big-box store, Bob Noyce, business cycle, Capital in the Twenty-First Century by Thomas Piketty, citizen journalism, Clayton Christensen, collapse of Lehman Brothers, collective bargaining, computer age, corporate raider, creative destruction, Credit Default Swap, crony capitalism, diversification, don't be evil, Donald Trump, Double Irish / Dutch Sandwich, Edward Snowden, Elon Musk, en.wikipedia.org, eurozone crisis, Fall of the Berlin Wall, family office, financial innovation, full employment, German hyperinflation, gig economy, Gini coefficient, Goldman Sachs: Vampire Squid, Google bus, Google Chrome, Gordon Gekko, income inequality, index fund, Innovator's Dilemma, intangible asset, invisible hand, Jeff Bezos, John Nash: game theory, John von Neumann, Joseph Schumpeter, Kenneth Rogoff, late capitalism, London Interbank Offered Rate, low skilled workers, Mark Zuckerberg, Martin Wolf, means of production, merger arbitrage, Metcalfe's law, multi-sided market, mutually assured destruction, Nash equilibrium, Network effects, new economy, Northern Rock, offshore financial centre, passive investing, patent troll, Peter Thiel, plutocrats, Plutocrats, prediction markets, prisoner's dilemma, race to the bottom, rent-seeking, road to serfdom, Robert Bork, Ronald Reagan, Sam Peltzman, secular stagnation, shareholder value, Silicon Valley, Skype, Snapchat, Social Responsibility of Business Is to Increase Its Profits, Steve Jobs, The Chicago School, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, too big to fail, undersea cable, Vanguard fund, very high income, wikimedia commons, William Shockley: the traitorous eight, zero-sum game

You don't need players to talk to each other to get collusion. Game theory has shown that firms are able to reach what look like cooperative outcomes on the basis of genuinely independent decisions.16 Many firms that have been caught continue to collude even after they no longer speak to each other.17 Tacit collusion can lead oligopolistic firms to achieve monopolistic outcomes, leading to reduced output, higher prices, and lower consumer welfare.18 This is known as the “oligopoly problem.” By allowing extreme industry concentration, the government has essentially guaranteed oligopolies can act like monopolies and encouraged outright and tacit collusion. Game theory applies to almost any interaction. Everyone has seen A Beautiful Mind. In the film John Nash, played by Russell Crowe, has an epiphany at a bar with his friends as they are trying to pick up women.

The solution to the problem of competition is called “Nash Equilibrium.” Nash didn't create game theory, but he developed it. His idea was a direct descendant of John von Neumann's Minimax theory. The idea is that players of a game won't seek to achieve the highest payout but will try to minimize their maximum loss. The easiest way to understand this is the example of a mother who allows her two children to divide a cake. The most equal division will happen if one cuts the cake and the other chooses the first piece. Each kid doesn't seek a theoretical bigger piece – he tries to minimize the chance he ends up with a really small one. Firms will often collude to avoid competition and minimize their maximum loss. That's what Nash was describing in the film with the blonde. There is much more to game theory than walking into a bar to talk to a blonde or dividing a cake.

There is much more to game theory than walking into a bar to talk to a blonde or dividing a cake. The most famous example in game theory is The Prisoner's Dilemma. If two prisoners are caught by the police and interrogated separately, they each have a difficult choice to make: to snitch or not to snitch. They can both be silent and not rat on each other. That is the best outcome for both. However, if one of them wants to improve his own lot, he might talk to the police and betray his friend. He might walk, and his friend will serve a longer sentence. There is no right answer to the Prisoner's Dilemma. If you play the game only once, you are highly motivated to betray your partner. However, completely different solutions begin to emerge if you play the game many times. In 1984 Robert Axelrod invited mathematicians, economists, and computer scientists to submit strategies for playing Prisoners' Dilemma.


pages: 304 words: 88,773

The Ghost Map: A Street, an Epidemic and the Hidden Power of Urban Networks. by Steven Johnson

call centre, clean water, correlation does not imply causation, creative destruction, Dean Kamen, digital map, double helix, edge city, germ theory of disease, global pandemic, Google Earth, Jane Jacobs, John Nash: game theory, John Snow's cholera map, lone genius, Louis Pasteur, mass immigration, megacity, mutually assured destruction, New Urbanism, nuclear winter, pattern recognition, peak oil, side project, Steven Pinker, Stewart Brand, The Death and Life of Great American Cities, the scientific method, trade route, unbiased observer, working poor

But somehow the nonstop traffic and bustle of Regent Street is almost imperceptible from the smaller lanes and alleys of western Soho, largely because there are very few conduits that open directly onto Regent Street. Walking around the neighborhood, it feels almost as if a barricade has been erected, keeping you from reaching the prominent avenue that you know is only a few feet away. And indeed, the street layout was explicitly designed to serve as a barricade. When John Nash designed Regent Street to connect Marylebone Park with the Prince Regent’s new home at Carlton House, he planned the thoroughfare as a kind of cordon sanitaire separating the well-to-do of Mayfair from the growing working-class community of Soho. Nash’s explicit intention was to create “a complete separation between the streets occupied by the Nobility and Gentry, and the narrower Streets and meaner houses occupied by mechanics and the trading part of the community.… My purpose was that the new street should cross the eastern entrance to all the streets occupied by the higher classes and to leave out to the east all the bad streets.”

On a planet of more than 6 billion people, there have to be thousands and thousands of lost souls ready and willing to detonate one of those weapons in a crowded urban center. How long before those two sets intersect? That driver with the rigged SUV isn’t going to be deterred by the conventional logic of détente-era nuclear politics. Mutually assured destruction isn’t much of a deterrent to him. Mutually assured destruction, in fact, sounds like a pretty good outcome. Game theory has always had trouble accounting for players with no rational self-interest, and the theories of nuclear deterrence are no exception. And once the bomb goes off, there’s no second line of defense—no vaccines or quarantines to block off the worst-case scenario. There will be maps, but they’ll be maps of incineration and fallout and mass graves. They won’t help us understand the threat the way Snow’s map helped us understand cholera.


pages: 416 words: 112,268

Human Compatible: Artificial Intelligence and the Problem of Control by Stuart Russell

3D printing, Ada Lovelace, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Alfred Russel Wallace, Andrew Wiles, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, augmented reality, autonomous vehicles, basic income, blockchain, brain emulation, Cass Sunstein, Claude Shannon: information theory, complexity theory, computer vision, connected car, crowdsourcing, Daniel Kahneman / Amos Tversky, delayed gratification, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Ernest Rutherford, Flash crash, full employment, future of work, Gerolamo Cardano, ImageNet competition, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of the wheel, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John Nash: game theory, John von Neumann, Kenneth Arrow, Kevin Kelly, Law of Accelerating Returns, Mark Zuckerberg, Nash equilibrium, Norbert Wiener, NP-complete, openstreetmap, P = NP, Pareto efficiency, Paul Samuelson, Pierre-Simon Laplace, positional goods, probability theory / Blaise Pascal / Pierre de Fermat, profit maximization, RAND corporation, random walk, Ray Kurzweil, recommendation engine, RFID, Richard Thaler, ride hailing / ride sharing, Robert Shiller, Robert Shiller, Rodney Brooks, Second Machine Age, self-driving car, Shoshana Zuboff, Silicon Valley, smart cities, smart contracts, social intelligence, speech recognition, Stephen Hawking, Steven Pinker, superintelligent machines, Thales of Miletus, The Future of Employment, Thomas Bayes, Thorstein Veblen, transport as a service, Turing machine, Turing test, universal basic income, uranium enrichment, Von Neumann architecture, Wall-E, Watson beat the top human players on Jeopardy!, web application, zero-sum game

(See the notes for the complete analysis.24) The general criterion is very simple, however: Alice’s strategy is the best she can devise, assuming that Bob’s is fixed. Bob’s strategy is the best he can devise, assuming that Alice’s is fixed. If both conditions are satisfied, we say that the strategies are in equilibrium. This kind of equilibrium is called a Nash equilibrium in honor of John Nash, who, in 1950 at the age of twenty-two, proved that such an equilibrium exists for any number of agents with any rational preferences and no matter what the rules of the game might be. After several decades’ struggle with schizophrenia, Nash eventually recovered and was awarded the Nobel Memorial Prize in Economics for this work in 1994. For Alice and Bob’s soccer game, there is only one equilibrium.

And without probabilities, the definition of rational action as maximizing expected utility isn’t applicable. As soon as someone else comes along, then, an agent will need some other way to make rational decisions. This is where game theory comes in. Despite its name, game theory isn’t necessarily about games in the usual sense; it’s a general attempt to extend the notion of rationality to situations with multiple agents. This is obviously important for our purposes, because we aren’t planning (yet) to build robots that live on uninhabited planets in other star systems; we’re going to put the robots in our world, which is inhabited by us. To make it clear why we need game theory, let’s look at a simple example: Alice and Bob playing soccer in the back garden (figure 3). Alice is about to take a penalty kick and Bob is in goal. Alice is going to shoot to Bob’s left or to his right.

None of these behaviors make sense when performing surgery in isolation, so IRL algorithms will not be able to interpret the preferences they imply. For this reason, we will need to generalize IRL from the single-agent setting to the multi-agent setting—that is, we will need to devise learning algorithms that work when the human and robot are part of the same environment and interacting with each other. With a human and a robot in the same environment, we are in the realm of game theory—just as in the penalty shoot-out between Alice and Bob on this page. We assume, in this first version of the theory, that the human has preferences and acts according to those preferences. The robot doesn’t know what preferences the human has, but it wants to satisfy them anyway. We’ll call any such situation an assistance game, because the robot is, by definition, supposed to be helpful to the human.10 Assistance games instantiate the three principles from the preceding chapter: the robot’s only objective is to satisfy human preferences, it doesn’t initially know what they are, and it can learn more by observing human behavior.


pages: 409 words: 105,551

Team of Teams: New Rules of Engagement for a Complex World by General Stanley McChrystal, Tantum Collins, David Silverman, Chris Fussell

Airbus A320, Albert Einstein, Atul Gawande, autonomous vehicles, bank run, barriers to entry, Black Swan, butterfly effect, call centre, Captain Sullenberger Hudson, Chelsea Manning, clockwork universe, crew resource management, crowdsourcing, Edward Snowden, Flash crash, Frederick Winslow Taylor, global supply chain, Henri Poincaré, high batting average, interchangeable parts, invisible hand, Isaac Newton, Jane Jacobs, job automation, job satisfaction, John Nash: game theory, knowledge economy, Mark Zuckerberg, Mohammed Bouazizi, Nate Silver, Pierre-Simon Laplace, RAND corporation, self-driving car, Silicon Valley, Silicon Valley startup, Skype, Steve Jobs, supply-chain management, The Wealth of Nations by Adam Smith, urban sprawl, US Airways Flight 1549, WikiLeaks, zero-sum game

The daily O&I briefing lay at the core of our transformation: this pumped information about the entire scope of our operations out to all members of the Task Force and partner agencies, and also offered everyone the chance to contribute. CHAPTER 9 BEATING THE PRISONER’S DILEMMA In one of the most memorable scenes from Ron Howard’s 2001 movie A Beautiful Mind, the protagonist—mathematician John Nash, played by Russell Crowe—is sitting with three colleagues in a Princeton bar when four women walk through the door. One of them, referred to only as “the blonde,” is breathtakingly beautiful. One sultry glance from her over to the mathematicians’ table and the men are convinced that she is interested—but who is to be the lucky man? Jokingly, one asks, “Shall we say swords, gentlemen? Pistols at dawn?”

With a faint grin, he says, “It’s the only way we win,” then runs out of the bar to spend the night alone recording his epiphany. This fictionalized episode provides a good introduction to one of the major ideas of game theory: while Adam Smith has led us to believe that, as movie-Nash summarizes it, “the best result comes from everyone in the group doing what’s best for himself,” movie-Nash adds that there are times when “the best result would come from everyone in the group doing what’s best for themselves . . . and the group.” • • • This basic tenet of game theory is also illustrated by the Prisoner’s Dilemma. In this famous thought experiment, two criminals—coconspirators—are arrested. They are taken to separate cells and interrogated. Both are offered the same deal: if you stay silent you’ll be sentenced to one year; if you rat on your partner you’ll go free; but if your partner rats on you, you’ll serve two years.

Part III: Sharing looks at how to deal with the continual change and dramatically increasing complexity that whipsaws us at breakneck speed. From the launch pad of NASA’s famed Apollo project that put the first human on the moon, to a blacked-out helicopter putting an Army Special Forces operator on a roof in Fallujah, the reader is introduced to shared consciousness: the way transparency and communication can be used in an organization to produce extraordinary outcomes across even large groups. And the Prisoner’s Dilemma and game theory will illustrate how the simple concept of trust is, in large organizations, anything but simple to create. Part IV: Letting Go probes the history, advantages, and imperatives of truly empowered execution in an organization—pushing decision making and ownership to the right level for every action. The reader will follow Commodore Perry’s hulking warships to the coast of Japan and awake with me in Iraq to make on-the-spot decisions on who will live, and who will not.


pages: 407 words: 104,622

The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution by Gregory Zuckerman

affirmative action, Affordable Care Act / Obamacare, Albert Einstein, Andrew Wiles, automated trading system, backtesting, Bayesian statistics, beat the dealer, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, blockchain, Brownian motion, butter production in bangladesh, buy and hold, buy low sell high, Claude Shannon: information theory, computer age, computerized trading, Credit Default Swap, Daniel Kahneman / Amos Tversky, diversified portfolio, Donald Trump, Edward Thorp, Elon Musk, Emanuel Derman, endowment effect, Flash crash, George Gilder, Gordon Gekko, illegal immigration, index card, index fund, Isaac Newton, John Meriwether, John Nash: game theory, John von Neumann, Loma Prieta earthquake, Long Term Capital Management, loss aversion, Louis Bachelier, mandelbrot fractal, margin call, Mark Zuckerberg, More Guns, Less Crime, Myron Scholes, Naomi Klein, natural language processing, obamacare, p-value, pattern recognition, Peter Thiel, Ponzi scheme, prediction markets, quantitative hedge fund, quantitative trading / quantitative finance, random walk, Renaissance Technologies, Richard Thaler, Robert Mercer, Ronald Reagan, self-driving car, Sharpe ratio, Silicon Valley, sovereign wealth fund, speech recognition, statistical arbitrage, statistical model, Steve Jobs, stochastic process, the scientific method, Thomas Bayes, transaction costs, Turing machine

He had decided that sports was overemphasized in society, and he was no longer going to pretend to care. The Massachusetts Institute of Technology became an obvious choice. “When I heard MIT didn’t have a football team, I knew it was the school for me,” he says. Moving to Cambridge, Massachusetts, Berlekamp dabbled in physics, economics, computers, and chemistry. As a freshman, he was selected to participate in an advanced calculus class taught by John Nash, the game theorist and mathematician who later would be immortalized in Sylvia Nasar’s book A Beautiful Mind. One day, in early 1959, Nash was lecturing at the chalkboard when a student raised his hand to ask a question. Nash turned to him and stared intensely. After several minutes of awkward silence, Nash pointed a finger at the student, berating him for having the temerity to interrupt his lecture.

Berlekamp and a few friends liked to grab pencils and paper to create boards of dots. They’d take turns adding lines, linking dots, and closing squares, playing dots and boxes, a century-old strategy game popular at the time in the Midwest. Some viewed the game as simple child’s play, but dots and boxes has surprising complexity and mathematical underpinnings, something Berlekamp came to appreciate later in life. “It was an early education in game theory,” Berlekamp says. By the time Berlekamp entered Fort Thomas Highlands High School, in 1954, he was a wiry five-foot-ten-inch young man with a good idea of what he enjoyed inside and outside the classroom. In school, it was mostly math and science. Detecting an intelligence that stood out from others, his classmates elected Berlekamp class president. He had curiosity about other subjects, too, though a passion for literature was mostly extinguished by a teacher who insisted on spending half the semester analyzing the novel Gone With the Wind.

Berlekamp’s apology led to an introduction to a student from England named Jennifer Wilson, whom he married in 1966.1 Berlekamp became an expert in decoding digital information, helping NASA decipher images coming back from satellites exploring Mars, Venus, and other parts of the solar system. Employing principles he had developed studying puzzles and games, like dots and boxes, Berlekamp cofounded a branch of mathematics called combinatorial game theory and wrote a book called Algebraic Coding Theory, a classic in the field. He also constructed an algorithm, appropriately named Berlekamp’s algorithm, for the factorization of polynomials over finite fields, which became a crucial tool in cryptography and other fields. Berlekamp wasn’t nearly as capable at navigating campus politics, as he soon found himself caught in a raging turf war between departments in Berkeley’s College of Letters and Science.


Super Thinking: The Big Book of Mental Models by Gabriel Weinberg, Lauren McCann

affirmative action, Affordable Care Act / Obamacare, Airbnb, Albert Einstein, anti-pattern, Anton Chekhov, autonomous vehicles, bank run, barriers to entry, Bayesian statistics, Bernie Madoff, Bernie Sanders, Black Swan, Broken windows theory, business process, butterfly effect, Cal Newport, Clayton Christensen, cognitive dissonance, commoditize, correlation does not imply causation, crowdsourcing, Daniel Kahneman / Amos Tversky, David Attenborough, delayed gratification, deliberate practice, discounted cash flows, disruptive innovation, Donald Trump, Douglas Hofstadter, Edward Lorenz: Chaos theory, Edward Snowden, effective altruism, Elon Musk, en.wikipedia.org, experimental subject, fear of failure, feminist movement, Filter Bubble, framing effect, friendly fire, fundamental attribution error, Gödel, Escher, Bach, hindsight bias, housing crisis, Ignaz Semmelweis: hand washing, illegal immigration, income inequality, information asymmetry, Isaac Newton, Jeff Bezos, John Nash: game theory, lateral thinking, loss aversion, Louis Pasteur, Lyft, mail merge, Mark Zuckerberg, meta analysis, meta-analysis, Metcalfe’s law, Milgram experiment, minimum viable product, moral hazard, mutually assured destruction, Nash equilibrium, Network effects, nuclear winter, offshore financial centre, p-value, Parkinson's law, Paul Graham, peak oil, Peter Thiel, phenotype, Pierre-Simon Laplace, placebo effect, Potemkin village, prediction markets, premature optimization, price anchoring, principal–agent problem, publication bias, recommendation engine, remote working, replication crisis, Richard Feynman, Richard Feynman: Challenger O-ring, Richard Thaler, ride hailing / ride sharing, Robert Metcalfe, Ronald Coase, Ronald Reagan, school choice, Schrödinger's Cat, selection bias, Shai Danziger, side project, Silicon Valley, Silicon Valley startup, speech recognition, statistical model, Steve Jobs, Steve Wozniak, Steven Pinker, survivorship bias, The Present Situation in Quantum Mechanics, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, transaction costs, uber lyft, ultimatum game, uranium enrichment, urban planning, Vilfredo Pareto, wikimedia commons

The rub is that if your co-conspirator follows the same strategy, you both go away for much longer than if you both just remained silent (five years versus one year). Hence the dilemma: do you risk their betrayal, or can you trust their solidarity and emerge with a small sentence? The dual betrayal with its dual five-year sentences is known as the Nash equilibrium of this game, named after mathematician John Nash, one of the pioneers of game theory and the subject of the biopic A Beautiful Mind. The Nash equilibrium is a set of player choices for which a change of strategy by any one player would worsen their outcome. In this case, the Nash equilibrium is the strategy of dual betrayals, because if either player instead chose to remain silent, that player would get a longer sentence. To both get a shorter sentence, they’d have to act cooperatively, coordinating their strategies.

(Sometimes people also say crossing the Rubicon, referencing Julius Caesar’s crossing of the Rubicon River with his troops in 49 B.C., deliberately breaking Roman law, making armed conflict inevitable and ultimately leading to him becoming dictator of Rome.) Game theory can again help you work through your potential exit strategies, assessing likely long-term outcomes and evaluating how various tactics might affect them. While not all situations parallel game-theory models (like the prisoner’s dilemma or the ultimatum game), most can still fruitfully be examined through a game-theory lens. In any conflict, whether in the endgame stage or otherwise, we encourage you to list the choices currently available to all the “players,” along with the consequences and payoffs. This method should help you decide whether a game is worth playing (or continuing), how to approach playing it, and whether there is some way to change the game so the outcome leans in your favor.

We hope that after reading it, you will be equipped to emerge from any adversarial situation with the best outcome for yourself. PLAYING THE GAME Game theory is the study of strategy and decision making in adversarial situations, and it provides several foundational mental models to help you think critically about conflict. Game in this context refers to a simplified version of a conflict, in which players engage in an artificial scenario with well-defined rules and quantifiable outcomes, much like a board game. In most familiar games—chess, poker, baseball, Monopoly, etc.—there are usually winners and losers. However, game theorists recognize that in real-life conflicts there isn’t always a clear winner or a clear loser. In fact, sometimes everyone playing the game can win and other times everyone can lose. The most famous “game” from game theory is called the prisoner’s dilemma. It can be used to illustrate useful game-theory concepts and can also be adapted to many life situations, including the arms race.


pages: 394 words: 108,215

What the Dormouse Said: How the Sixties Counterculture Shaped the Personal Computer Industry by John Markoff

Any sufficiently advanced technology is indistinguishable from magic, Apple II, back-to-the-land, beat the dealer, Bill Duvall, Bill Gates: Altair 8800, Buckminster Fuller, California gold rush, card file, computer age, computer vision, conceptual framework, cuban missile crisis, different worldview, Donald Knuth, Douglas Engelbart, Douglas Engelbart, Dynabook, Edward Thorp, El Camino Real, Electric Kool-Aid Acid Test, general-purpose programming language, Golden Gate Park, Hacker Ethic, hypertext link, informal economy, information retrieval, invention of the printing press, Jeff Rulifson, John Markoff, John Nash: game theory, John von Neumann, Kevin Kelly, knowledge worker, Mahatma Gandhi, Menlo Park, Mother of all demos, Norbert Wiener, packet switching, Paul Terrell, popular electronics, QWERTY keyboard, RAND corporation, RFC: Request For Comment, Richard Stallman, Robert X Cringely, Sand Hill Road, Silicon Valley, Silicon Valley startup, South of Market, San Francisco, speech recognition, Steve Crocker, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, Ted Nelson, The Hackers Conference, Thorstein Veblen, Turing test, union organizing, Vannevar Bush, Whole Earth Catalog, William Shockley: the traitorous eight

He watched the Moscow show trials of the early fifties, hoping that the abuses of the Soviets would moderate. In the end, because he had left home, he was able to quit the party without being embarrassed or embarrassing his family. At Princeton, McCarthy was a contemporary of John Nash, who later won a Nobel Prize in economics for his work in game theory, and whose life was chronicled by Sylvia Nasar in A Beautiful Mind. As graduate students, McCarthy, Nash, and several of the other students enjoyed constantly scheming and playing practical jokes on one another, justifying their antics in terms of their game-theory explorations. McCarthy arrived at Stanford for the second time (he had taught math there briefly in the early fifties) as a thirty-five-year-old former wunderkind who had invented the term “artificial intelligence.” While teaching math at Dartmouth during the summer of 1956, he had been the principal organizer of the first conference on modeling intelligence in computers and coined the term as part of the conference proposal.


pages: 415 words: 125,089

Against the Gods: The Remarkable Story of Risk by Peter L. Bernstein

"Robert Solow", Albert Einstein, Alvin Roth, Andrew Wiles, Antoine Gombaud: Chevalier de Méré, Bayesian statistics, Big bang: deregulation of the City of London, Bretton Woods, business cycle, buttonwood tree, buy and hold, capital asset pricing model, cognitive dissonance, computerized trading, Daniel Kahneman / Amos Tversky, diversified portfolio, double entry bookkeeping, Edmond Halley, Edward Lloyd's coffeehouse, endowment effect, experimental economics, fear of failure, Fellow of the Royal Society, Fermat's Last Theorem, financial deregulation, financial innovation, full employment, index fund, invention of movable type, Isaac Newton, John Nash: game theory, John von Neumann, Kenneth Arrow, linear programming, loss aversion, Louis Bachelier, mental accounting, moral hazard, Myron Scholes, Nash equilibrium, Norman Macrae, Paul Samuelson, Philip Mirowski, probability theory / Blaise Pascal / Pierre de Fermat, random walk, Richard Thaler, Robert Shiller, Robert Shiller, spectrum auction, statistical model, stocks for the long run, The Bell Curve by Richard Herrnstein and Charles Murray, The Wealth of Nations by Adam Smith, Thomas Bayes, trade route, transaction costs, tulip mania, Vanguard fund, zero-sum game

The opposite view would prevail among the politicians. Looking downward vertically, we find that both the choices rank higher than 4: the politicians would rather do nothing or run a deficit than follow a policy that cost them their jobs if their constituents lose their jobs as a result. This outcome is known as a Nash Equilibrium, named after John Nash, another Princetonian and one of the 1994 winners of the Nobel Prize for his contributions to game theory.18 Under the Nash Equilibrium the outcome, though stable, is less than optimal. Both sides would obviously prefer almost anything to this one. Yet they cannot reach a better bargain unless they drop their adversarial positions and work together on a common policy that would give each a supportive, or at least a neutral, role that would keep them from getting into each other's way.

The theory focuses on decision-making, but bears little resemblance to the many other theories that originated in games of chance. Despite its nineteenth-century forebears, game theory represents a dramatic break from earlier efforts to incorporate mathematical inevitability into decision-making. In the utility theories of both Daniel Bernoulli and Jevons, the individual makes choices in isolation, unaware of what others might be doing. In game theory, however, two or more people try to maximize their utility simultaneously, each aware of what the others are about. Game theory brings a new meaning to uncertainty. Earlier theories accepted uncertainty as a fact of life and did little to identify its source. Game theory says that the true source of uncertainty lies in the intentions of others. From the perspective of game theory, almost every decision we make is the result of a series of negotiations in which we try to reduce uncertainty by trading off what other people want in return for what we want ourselves.

."*' Another contemporary recalls that the Princeton economics department `just hated Oskar."9 Morgenstern himself complained about the lack of attention his beloved masterpiece received from others. After visiting Harvard in 1945 he noted "none of them" had any interest in game theory.10 He reported in 1947 that a fellow economist named Ropke said that game theory "was Viennese coffeehouse gossip."t When he visited a group of distinguished economists in Rotterdam in 1950, he discovered that they "wanted to know nothing about [game theory] because it disturbs them." Although an enthusiast for the uses of mathematics in economic analysis-he despised Keynes's nonrigorous treatment of expectations and described The General Theory as "simply horrible"-Morgenstern complained constantly about his problems with the advanced material into which von Neumann had lured him.11 Throughout their collaboration Morgenstern held von Neumann in awe.


pages: 396 words: 116,332

Political Ponerology (A Science on the Nature of Evil Adjusted for Political Purposes) by Andrew M. Lobaczewski

anti-communist, corporate raider, en.wikipedia.org, John Nash: game theory, means of production, phenotype, Project for a New American Century

In a unique and probing synthesis of science and mysticism she presents a detailed series of case studies and application of her hypothesis of hyperdimensional influence. From interpersonal relationships and their expression of archetypal dramas to the vectoring of human behaviour to achieve hyperdimensional purposes, Almost Human reveals the mechanics of evil, how it creeps into our lives, and what we need to be aware of in order to avoid it. The case studies of John Nash, the schizoidal creator of Game Theory, and Ira Einhorn, the New Age psychopath who murdered his girlfriend, are the window through which Knight-Jadczyk unravels the intricate web of deception, aims, and counter-aims of the Powers That Be. Almost Human is essential reading for anyone wondering why our world is becoming increasingly controlled and our freedoms more restricted. The Wave 8 - “Debugging the Universe” … The Hero’s Journey The Path of the Fool, the Hero’s Journey, the Great Work - by whatever name it takes, the path of self-development and growth of knowledge is one fraught with difficult lessons and intense struggle.

Braithwaite’s work in the philosophy of the physical sciences was important for his theories on the nature of scientific inductive reasoning and the use of models, as well as on the use of probabilistic laws. He also applied his scientific background to his studies of moral and religious philosophy, particularly in the application of mathematical game theory. In his book Theory of Games as a Tool for the Moral Philosopher (1955), he demonstrated the ways in which game theory could be used to arrive at moral choices and ethical decisions. His classic work was Scientific Explanation: A Study of Theory, Probability and Law in Science (1953), on the methodology of natural science. (Encyclopaedia Britannica Online, http://www.britannica.com/ eb/article-9016188/RB-Braithwaite) [Editor’s note.] * * * [6]: G.


pages: 374 words: 114,600

The Quants by Scott Patterson

Albert Einstein, asset allocation, automated trading system, beat the dealer, Benoit Mandelbrot, Bernie Madoff, Bernie Sanders, Black Swan, Black-Scholes formula, Blythe Masters, Bonfire of the Vanities, Brownian motion, buttonwood tree, buy and hold, buy low sell high, capital asset pricing model, centralized clearinghouse, Claude Shannon: information theory, cloud computing, collapse of Lehman Brothers, collateralized debt obligation, commoditize, computerized trading, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, Donald Trump, Doomsday Clock, Edward Thorp, Emanuel Derman, Eugene Fama: efficient market hypothesis, fixed income, Gordon Gekko, greed is good, Haight Ashbury, I will remember that I didn’t make the world, and it doesn’t satisfy my equations, index fund, invention of the telegraph, invisible hand, Isaac Newton, job automation, John Meriwether, John Nash: game theory, Kickstarter, law of one price, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, margin call, merger arbitrage, money market fund, Myron Scholes, NetJets, new economy, offshore financial centre, old-boy network, Paul Lévy, Paul Samuelson, Ponzi scheme, quantitative hedge fund, quantitative trading / quantitative finance, race to the bottom, random walk, Renaissance Technologies, risk-adjusted returns, Robert Mercer, Rod Stewart played at Stephen Schwarzman birthday party, Ronald Reagan, Sergey Aleynikov, short selling, South Sea Bubble, speech recognition, statistical arbitrage, The Chicago School, The Great Moderation, The Predators' Ball, too big to fail, transaction costs, value at risk, volatility smile, yield curve, éminence grise

He contacted Baldwin and requested the data behind the strategy. It arrived in the spring of 1959, just before Thorp moved from UCLA to the Massachusetts Institute of Technology. At MIT, Thorp found a hotbed of intellectual creativity that was quietly revolutionizing modern society. The job he stepped into, the coveted position of C. L. E. Moore Instructor, had previously been held by John Nash, the math prodigy who eventually won the Nobel Prize in economics in 1994 for his work on game theory, a mathematical approach to how people compete and cooperate. (Nash later became known as the subject of A Beautiful Mind, the book and movie about the competing forces of his genius and mental illness.) That first summer in Cambridge, Thorp crunched the numbers on blackjack, slowly evolving what would become a historic breakthrough in the game.

In the mid-1980s, Simons and Ax spun a fund out of Monemetrics called Axcom Ltd. In 1985, Ax moved the operation to Huntington Beach, California. Axcom was to act as the trading advisor for the fund, which was nominally run as an investing firm owned by a company Simons had founded in July 1982 called Renaissance Technologies. Soon Simons’s growing crew of quants added another math wizard, Elwyn Berlekamp, a game theory expert at Berkeley. Like Ed Thorp, Berlekamp had worked with Claude Shannon and John Kelly at MIT. He’d briefly met Simons during a stint at IDA in the 1960s. The fund put up solid returns for several years, even managing to trade through Black Monday with relatively little damage. In 1988, Ax and Simons renamed the fund Medallion in honor of a math award they’d both won. Almost as soon as they’d renamed the fund, things started going south for Medallion.

The fund had a rough start, but it eventually started hitting on all cylinders. In 1997, it was absorbed into the Medallion mother ship and called the Factor Nova Funds, adding stat arb firepower to an already state-of-the-art investment machine. It was the first step in making Medallion a genuine multistrategy fund. By then, Berlekamp was gone. He’d left Renaissance at the end of 1990 to pursue academic interests at Berkeley, where he went on to crack game theory puzzlers such as mathematical chess. But the Medallion legend continued to grow. To be sure, the fund has had a few hiccups over the years. In March 2000, when the dot-com bubble began to implode, reversing trends in technology stocks that had been in place for several years, Medallion lost $250 million in three days, nearly wiping out its year-to-date profit. But the fund quickly bounced back and put up another year of stellar returns.


Theory of Games and Economic Behavior: 60th Anniversary Commemorative Edition (Princeton Classic Editions) by John von Neumann, Oskar Morgenstern

Albert Einstein, business cycle, collective bargaining, full employment, Isaac Newton, John Nash: game theory, John von Neumann, linear programming, Nash equilibrium, Parkinson's law, Paul Samuelson, profit motive, RAND corporation, the market place, zero-sum game

Afterword ARIEL RUBINSTEIN During the past ten years Princeton University Press has done a remarkable job of republishing, in a beautiful and eye-catching format, many of the seminal works from the early days of game theory at Princeton. This new printing of Theory of Games and Economic Behavior, marking the book’s sixtieth anniversary, continues the celebration of game theory. Since the original publication of the book, game theory has moved from the fringe of economics into its mainstream. The distinction between economic theorist and game theorist has virtually disappeared. The 1994 Nobel Prize awarded to John Nash, John Harsanyi, and Reinhard Selten was viewed not just as recognition of three great scholars but also as a victory for game theory as a discipline. Evidence of the immense importance of this book in the development of game theory is the fact that, notwithstanding the intense search for the ancient origins of its ideas, there is consensus that the book was the first major publication in the field.

Given such prevailing views, there was no incentive or opportunity for graduate students and junior faculty to study the theory of games. As a consequence, the theory of games was developed almost exclusively by mathematicians in this period. To describe the spirit of the time as seen by another outside observer, we shall paraphrase a section of Robert J. Aumann’s magnificent article on game theory from The New Palgrave Dictionary of Economics [14]. The period of the late ’40s and early ’50s was a period of excitement in game theory. The discipline had broken out of its cocoon and was testing its wings. Giants walked the earth. At Princeton, John Nash laid the groundwork for the general non-cooperative theory and for cooperative bargaining theory. Lloyd Shapley defined a value for coalitional games, initiated the theory of stochastic games, coinvented the core with D. B. Gillies, and together with John Milnor developed the first game models with an infinite number of players.

It identifies patterns of reasoning and investigates their implications on decision making in strategic situations. According to this opinion, game theory does not have normative implications and its empirical significance is very limited. Game theory is viewed as a cousin of logic. Logic does not allow us to screen out true statements from false ones and does not help us distinguish right from wrong. Game theory does not tell us which action is preferable or predict what other people will do. If game theory is nevertheless useful or practical, it is only indirectly so. In any case, lhe burden of proof is on those who use game theory to make policy recommendations, not on those who doubt the practical value of game theory in the first place. And, by the way, I sometimes wonder why people are so obsessed in looking for “usefulness” in economics generally and in game theory in particular. Should academic research be judged by its usefulness?


pages: 377 words: 121,996

Live and Let Spy: BRIXMIS - the Last Cold War Mission by Steve Gibson

Berlin Wall, British Empire, corporate social responsibility, cuban missile crisis, Fall of the Berlin Wall, John Nash: game theory, libertarian paternalism, long peace, means of production, Mikhail Gorbachev, moral panic, mutually assured destruction, RAND corporation, road to serfdom, Ronald Reagan, unbiased observer, WikiLeaks

The theory formed the basis of a new political control, from advertising to psychology, convinced that all of human activity could be understood by mathematical models and equations. Its most depressing manifestation today is government’s moralising intervention in every aspect of private life – drinking, eating, leisure, health, children – that would have been unconscionable just thirty years ago. The brilliant, paranoid-schizophrenic, and Nobel Prize-winning mathematician largely responsible for this development, John Nash, called it ‘Game Theory’. The underlying assumption of Game Theory was that a fearful and suspicious human being would always be inclined to maximise self-interest over any alternative altruistic, collective or collaborative action. The sum of these individual self-interests would in turn create a fearful equilibrium – control – across society that out-weighed the alternative – chaos. Late 1970s Britain, and the incoming Thatcher administration, experimented further with the idea of fearful, rational, self-interest as the single explanation of human behaviour.

It was compounded by an imploding political left incapable of true political activity in the sense of acting together in a common cause beyond selfish opportunism. Indeed, the very notion of the public – a self-conscious body operating in a cohesive and collective interest – became redundant. Yet, many proponents of Game Theory themselves recognise the limitations: simplistic assumptions about human nature; a wilful dismissal of free will; and, stubborn acts of unrequited altruism, philanthropy and self-sacrifice all served to defeat the predicted outcomes of Game Theory calculations – the management of human beings by numbers continues to preside over a rise in inequality and the diminution of social mobility within Western societies, rather than liberate them. The idea that, through the pursuit of targets, league tables and pseudo-science we could become free from bureaucratic elites, free to choose our own lives, and free from the constraints of class, income, privilege or socially pre-destined roles, proved to be a fantasy.

Yet, Live and Let Spy also argues that, while Cold War warriors fought a tyrannical and ruthless version of Communism abroad, they remained ignorant of – and lost – an ideological battle at home. That battle saw government and business come to dominate the expectations of their populations in the post-WWII world. This political ideology was fuelled by the construction of a convenient ‘enemy’ abroad, while utilising the Cold War’s Game Theory and Freudian-based public relations management to tame the irrational, self-serving, unconscious nature of individuals at home. Gibson argues that in doing so, liberal democracies traduced power to construct regimes of vacuous politics and ‘negative’ freedom, absent of purpose, meaning, and moral autonomy. Intelligence became complicit and so aligned in this progression such that, by 2003, it supinely offered a version of truth to power that power demanded to hear.


pages: 561 words: 120,899

The Theory That Would Not Die: How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant From Two Centuries of Controversy by Sharon Bertsch McGrayne

Bayesian statistics, bioinformatics, British Empire, Claude Shannon: information theory, Daniel Kahneman / Amos Tversky, double helix, Edmond Halley, Fellow of the Royal Society, full text search, Henri Poincaré, Isaac Newton, Johannes Kepler, John Markoff, John Nash: game theory, John von Neumann, linear programming, longitudinal study, meta analysis, meta-analysis, Nate Silver, p-value, Pierre-Simon Laplace, placebo effect, prediction markets, RAND corporation, recommendation engine, Renaissance Technologies, Richard Feynman, Richard Feynman: Challenger O-ring, Robert Mercer, Ronald Reagan, speech recognition, statistical model, stochastic process, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, traveling salesman, Turing machine, Turing test, uranium enrichment, Yom Kippur War

In economics and finance Bayes appears at multiple levels, ranging from theoretical mathematics and philosophy to nitty-gritty money making. The method figured prominently in three Nobel Prizes awarded for theoretical economics, in 1990, 1994, and 2004. The first Nobel involved the Italian Bayesian de Finetti, who anticipated the Nobel Prize–winning work of Harry Markowitz by more than a decade. Mathematical game theorists John C. Harsanyi and John Nash (the latter the subject of a book and movie, A Beautiful Mind) shared a Bayesian Nobel in 1994. Harsanyi often used Bayes to study competitive situations where people have incomplete or uncertain information about each other or about the rules. Harsanyi also showed that Nash’s equilibrium for games with incomplete or imperfect information was a form of Bayes’ rule. In 2002 Bayes won perhaps not an entire Nobel Prize but certainly part of one.

., 81, 82 Food and Drug Administration, 228–29 forensic science, 235–36 Fox, Robert, 35 Franco, Francisco, 190, 194 French Revolution, 29, 35–36 frequentism: Bayes’ rule accepted in, 233–34 Bayes’ rule compared empirically, 157–58, 159–61 business and, 141, 142 change points and, 216–17 computation and, 214, 225 Cornfield and, 116–17 decision theory and, 236 dimensionality and, 214 expert opinion and, 179 The Federalist papers and, 157–58, 159–61 genetic science and, 47–48 hypotheses and, 116–17, 142, 217, 234 image analysis and, 219 insurance and, 92, 94 likelihood principle and, 132, 233 Lindley’s Paradox and, 132–33 military and, 241 movies and, 178 nuclear weapons and, 123 philosophy and, 253–54 practical applications and, generally, 209 priors and, 104, 177 probability and, 36, 50, 55–57, 99, 130, 142, 145–46, 156, 170 social science and, 217 statistics and, 47–48, 87–88, 98–99, 104–5, 142, 214, 234, 253 Stein’s Paradox and, 131–32 subjectivity and, 104, 129 Tukey and, 169–70 uncertainty and, 55–57, 142 unified approach and, 170 Friedman, Milton, 102, 159, 235 Fuchs, Klaus, 85 gambling: astronomy and, 36 Bayes’ rule and, 11 beliefs and, 51–52 game theory, 236 at Harvard Business School, 148 Laplace and, 19, 20, 21, 32 probability and, 6, 9, 51–52 statistics and, 106–7 subjectivity and, 185 game theory, 236. See also gambling Gastwirth, Joseph L., 227 Gates, Bill, 242 Gauss, C. F., 102 Gelfand, Alan E., 220–22, 224–25 Geman, Donald, 218–19, 221 Geman, Stuart, 218–19, 221, 251 gender, x, 24–27 generating functions, 25 genetic science, xi, 45–48, 225, 235–36, 238–40 Gerrodette, Timothy, 230 Gibbs, Josiah Willard, 219 Gibbs sampling, 218–19, 221, 225–26 Gilbert, Edgar N., 169 Gillispie, Charles Coulston, 35 Gini, Corrado, 52 Gleason, Andrew, 83 God: Bayes’ rule and, ix, 10, 11, 253–54 cause-and-effect and, 5–6 evil and, 4 existence of, 177, 235 happiness and, 4 natural law and, 6, 30 probability and, 19–20.

The philosophical rationale for using Bayesian methods had been largely settled. It was becoming the only mathematics of uncertainty with an explicit, powerful, and secure foundation in logic. How to apply it, though, remained a controversial question. Lindley’s enormous influence as a teacher and organizer bore fruit in the generation to come, while Savage’s book spread Bayesian methods to the military and to business, history, game theory, psychology, and beyond. Although Savage wrote about rabbit ears and neon light in beer, he personally encouraged researchers who would apply Bayes’ rule to life-and-death problems. 8. jerome cornfield, lung cancer, and heart attacks Bayes came to medical research through the efforts of a single scientist, Jerome Cornfield, whose only degree was a B.A. in history and who relied on the rule to identify the causes of lung cancer and heart attacks.


pages: 412 words: 115,266

The Moral Landscape: How Science Can Determine Human Values by Sam Harris

Albert Einstein, banking crisis, Bayesian statistics, cognitive bias, end world poverty, endowment effect, energy security, experimental subject, framing effect, hindsight bias, impulse control, John Nash: game theory, longitudinal study, loss aversion, meta analysis, meta-analysis, out of africa, pattern recognition, placebo effect, Ponzi scheme, Richard Feynman, risk tolerance, scientific worldview, stem cell, Stephen Hawking, Steven Pinker, the scientific method, theory of mind, ultimatum game, World Values Survey

.), but because of their neurological and social deficits, they are doing a very bad job of it. We can say that a psychopath like Ted Bundy takes satisfaction in the wrong things, because living a life purposed toward raping and killing women does not allow for deeper and more generalizable forms of human flourishing. Compare Bundy’s deficits to those of a delusional physicist who finds meaningful patterns and mathematical significance in the wrong places. The mathematician John Nash, while suffering the symptoms of his schizophrenia, seems a good example: his “Eureka!” detectors were poorly calibrated; he saw meaningful patterns where his peers would not—and these patterns were a very poor guide to the proper goals of science (i.e., understanding the physical world). Is there any doubt that Ted Bundy’s “Yes! I love this!” detectors were poorly coupled to the possibilities of finding deep fulfillment in this life, or that his obsession with raping and killing young women was a poor guide to the proper goals of morality (i.e., living a fulfilling life with others)?

For the purposes of this discussion, however, it seems sufficient to point out that we are beginning to understand the kinds of brain pathologies that lead to the most extreme forms of human evil. And just as some people have obvious moral deficits, others must possess moral talent, moral expertise, and even moral genius. As with any human ability, these gradations must be expressed at the level of the brain. Game theory suggests that evolution probably selected for two stable orientations toward human cooperation: tit for tat (often called “strong reciprocity”) and permanent defection.91 Tit for tat is generally what we see throughout society: you show me some kindness, and I am eager to return the favor; you do something rude or injurious, and the temptation to respond in kind becomes difficult to resist. But consider how permanent defection would appear at the level of human relationships: the defector would probably engage in continuous cheating and manipulation, sham moralistic aggression (to provoke guilt and altruism in others), and strategic mimicry of positive social emotions like sympathy (as well as of negative emotions like guilt).

But consider how permanent defection would appear at the level of human relationships: the defector would probably engage in continuous cheating and manipulation, sham moralistic aggression (to provoke guilt and altruism in others), and strategic mimicry of positive social emotions like sympathy (as well as of negative emotions like guilt). This begins to sound like garden-variety psychopathy. The existence of psychopaths, while otherwise quite mysterious, would seem to be predicted by game theory. And yet, the psychopath who lives his entire life in a tiny village must be at a terrible disadvantage. The stability of permanent defection as a strategy would require that a defector be able to find people to fleece who are not yet aware of his terrible reputation. Needless to say, the growth of cities has made this way of life far more practicable than it has ever been. Evil When confronted with psychopathy at its most extreme, it is very difficult not to think in terms of good and evil.


pages: 436 words: 76

Culture and Prosperity: The Truth About Markets - Why Some Nations Are Rich but Most Remain Poor by John Kay

"Robert Solow", Albert Einstein, Asian financial crisis, Barry Marshall: ulcers, Berlin Wall, Big bang: deregulation of the City of London, business cycle, California gold rush, complexity theory, computer age, constrained optimization, corporate governance, corporate social responsibility, correlation does not imply causation, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, Donald Trump, double entry bookkeeping, double helix, Edward Lloyd's coffeehouse, equity premium, Ernest Rutherford, European colonialism, experimental economics, Exxon Valdez, failed state, financial innovation, Francis Fukuyama: the end of history, George Akerlof, George Gilder, greed is good, Gunnar Myrdal, haute couture, illegal immigration, income inequality, industrial cluster, information asymmetry, intangible asset, invention of the telephone, invention of the wheel, invisible hand, John Meriwether, John Nash: game theory, John von Neumann, Kenneth Arrow, Kevin Kelly, knowledge economy, light touch regulation, Long Term Capital Management, loss aversion, Mahatma Gandhi, market bubble, market clearing, market fundamentalism, means of production, Menlo Park, Mikhail Gorbachev, money: store of value / unit of account / medium of exchange, moral hazard, Myron Scholes, Naomi Klein, Nash equilibrium, new economy, oil shale / tar sands, oil shock, Pareto efficiency, Paul Samuelson, pets.com, popular electronics, price discrimination, price mechanism, prisoner's dilemma, profit maximization, purchasing power parity, QWERTY keyboard, Ralph Nader, RAND corporation, random walk, rent-seeking, Right to Buy, risk tolerance, road to serfdom, Ronald Coase, Ronald Reagan, second-price auction, shareholder value, Silicon Valley, Simon Kuznets, South Sea Bubble, Steve Jobs, telemarketer, The Chicago School, The Market for Lemons, The Nature of the Firm, the new new thing, The Predators' Ball, The Wealth of Nations by Adam Smith, Thorstein Veblen, total factor productivity, transaction costs, tulip mania, urban decay, Vilfredo Pareto, Washington Consensus, women in the workforce, yield curve, yield management

Von Neumann, born in Hungary, was one of the geniuses of his age. 19 At eighteen he was studying for three different degrees in different subjects at different universities in different countries. After making fundamental contributions to mathematics and quantum physics, he turned his attention briefly to economics, which he found "a million miles away from an advanced science." 20 Von Neumann became head of the U.S. Atomic Energy Commission-and the inspiration for Dr. Strangelove-before dying at the age of fifty-three. John Nash was author of the principal solution concept in game theory-the Nash equilibrium-but his productive career was ended by schizophrenia. His health partially restored, he was awarded the Nobel Prize in 1994. 21 Nash was played by Russell Crowe in an Oscar-winning film of his life, A Beautiful Mind. Institutional (or transactions cost) economics regards as its founder Ronald Coase,n a British economist who spent most of his career at the University of Chicago.

If Part III of the book was mostly concerned with these anonymous interactions, Part IV describes how the working of markets differs when these interactions are not anonymous. Game theory established mathematical Culture and Prosperity {205} tools for discussing strategic interrelationships in small groups and is essential for this analysis. 18 Game theory has a popular appeal that fixed-point theorems will never achieve. This is partly the product of larger-than-life examples. The Prisoner's Dilemma, the most preposterous but the best known of all contributions to game theory, will appear in chapter 21. Game theory's characters are also larger-than-life. Von Neumann, born in Hungary, was one of the geniuses of his age. 19 At eighteen he was studying for three different degrees in different subjects at different universities in different countries.

The Arrow-Debreu results are the culmination of a long tradition in economics that emphasizes supply and demand, perfectly competitive markets, and the search for market equilibrium, conducted by independent, self-regarding agents. Economic research since Arrow and Debreu has drawn game theory, transactions costs, and most recently behavioral economics into the mainstream of economic theory. In the Arrow-Debreu framework, interactions are anonymous and every market has many buyers and sellers. In game theory, the players are few and not anonymous. In the Arrow-Debreu framework, institutions do not exist or are dealt with in a reductionist way. Institutional, or transactions costs, economics recognizes that economic lives are lived in and through economic institutions. Behavioral economics contemplates alternative assumptions about motives and the nature of economic behavior. I will introduce game theory and institutional economics in the present chapter and take up behavioral economics in the chapter that follows.


pages: 500 words: 145,005

Misbehaving: The Making of Behavioral Economics by Richard H. Thaler

"Robert Solow", 3Com Palm IPO, Albert Einstein, Alvin Roth, Amazon Mechanical Turk, Andrei Shleifer, Apple's 1984 Super Bowl advert, Atul Gawande, Berlin Wall, Bernie Madoff, Black-Scholes formula, business cycle, capital asset pricing model, Cass Sunstein, Checklist Manifesto, choice architecture, clean water, cognitive dissonance, conceptual framework, constrained optimization, Daniel Kahneman / Amos Tversky, delayed gratification, diversification, diversified portfolio, Edward Glaeser, endowment effect, equity premium, Eugene Fama: efficient market hypothesis, experimental economics, Fall of the Berlin Wall, George Akerlof, hindsight bias, Home mortgage interest deduction, impulse control, index fund, information asymmetry, invisible hand, Jean Tirole, John Nash: game theory, John von Neumann, Kenneth Arrow, Kickstarter, late fees, law of one price, libertarian paternalism, Long Term Capital Management, loss aversion, market clearing, Mason jar, mental accounting, meta analysis, meta-analysis, money market fund, More Guns, Less Crime, mortgage debt, Myron Scholes, Nash equilibrium, Nate Silver, New Journalism, nudge unit, Paul Samuelson, payday loans, Ponzi scheme, presumed consent, pre–internet, principal–agent problem, prisoner's dilemma, profit maximization, random walk, randomized controlled trial, Richard Thaler, Robert Shiller, Robert Shiller, Ronald Coase, Silicon Valley, South Sea Bubble, Stanford marshmallow experiment, statistical model, Steve Jobs, Supply of New York City Cabdrivers, technology bubble, The Chicago School, The Myth of the Rational Market, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, transaction costs, ultimatum game, Vilfredo Pareto, Walter Mischel, zero-sum game

Here is another question for you: What is the Nash equilibrium for this scenario? Named for John Nash, the subject of the popular book (and biopic) A Beautiful Mind, the Nash equilibrium in this game is a number that if everyone guessed it, no one would want to change their guess. And the only Nash equilibrium in this game is zero. To see why, suppose everyone guessed 3. Then the average guess would be 3 and you would want to guess two-thirds of that, or 2. But if everyone guessed 2 you would want to guess 1.33, and so forth. If and only if all participants guessed zero would no one want to change his or her guess. Perhaps you have now formulated the question that might have been worth asking before submitting your guess: who are the other players, and how much math and game theory do they know? If you are playing at your local bar, especially late in the evening, other people are probably not thinking too deeply, so you might make a guess around 33.

Another was Robert Shiller, who appeared above and plays a starring role in the next section, and the third was Colin Camerer. I first met Colin when he was on the academic job market. At that point he had picked up an MBA and was nearly done with a PhD from the University of Chicago, and he had not yet turned twenty-one. Colin has made many important contributions to behavioral economics. Two stand out. First, he more or less invented the field of behavioral game theory, the study of how people actually play games, as opposed to standard game theory, which studies how Econs would play games if they knew that everyone else playing was also an Econ. More recently, he has been at the forefront of neuro-economics, which uses techniques such as brain imaging to learn more about how people make decisions. Colin has many talents. While still a teenager in grad school, he formed a record company and signed the famously satirical punk band called the Dead Milkmen.

S467. 168 “I tend to view”: Shiller (1986), p. S501. Chapter 18: Anomalies 169 The Structure of Scientific Revolutions: Kuhn (1962). 174 the first two columns: Thaler (1987a, 1987b). 174 A burst of papers: Rozeff and Kinney (1976). 174 Another anomaly came from bettors at the racetrack: Thaler (1992). Chapter 19: Forming a Team 176 game theory in the 1940s: The catalyst was arguably von Neumann and Morgenstern (1947), the first edition of which was published in 1944. 176 the field of behavioral game theory: Camerer (2003). 180 Stanley Schachter: Schachter et al. (1985a, 1985b), Hood et al. (1985). 180 generating new psychology of our own: An exception is the research associated with Sendhil Mullainathan and Eldar Shafir’s (2013) book Scarcity, one of those rare collaborations between an economist and a psychologist. 182 paper by Fehr that captured our attention: Fehr, Kirchsteiger, and Riedl (1993). 182 employment contracts could be viewed partially as a gift exchange: Akerlof (1982). 182 Rabin’s model: Rabin (1993). 20: Narrow Framing on the Upper East Side 186 bold forecasts and timid choices: Kahneman and Lovallo (1993). 186 described . . . in Thinking, Fast and Slow: Kahneman (2011), ch. 22. 189 benefits are demonstrably large: Mullainathan (2013), Baicker, Mullainathan, and Schwartzstein (2013). 191 equity premium puzzle: Mehra and Prescott (1985). 192 six years to get the paper published: Rajnish Mehra told me this. 192 none of the explanations had proven to be completely satisfactory: Mehra (2007). 194 words with one syllable: Samuelson (1979), p. 306. 194 “Risk and Uncertainty: A Fallacy of Large Numbers”: Samuelson (1963). 195 “myopic loss aversion”: Benartzi and Thaler (1995). 195 The only way you can ever take 100 attractive bets: Barberis, Huang and Santos (2001) formalize this intuition in a dynamic model. 195 experiment using recently hired non-faculty employees: Benartzi and Thaler (1999). 197 Quarterly Journal of Economics dedicated to Amos’s memory: Thaler et al. (1997). 198 A paper by . . .


pages: 461 words: 128,421

The Myth of the Rational Market: A History of Risk, Reward, and Delusion on Wall Street by Justin Fox

activist fund / activist shareholder / activist investor, Albert Einstein, Andrei Shleifer, asset allocation, asset-backed security, bank run, beat the dealer, Benoit Mandelbrot, Black-Scholes formula, Bretton Woods, Brownian motion, business cycle, buy and hold, capital asset pricing model, card file, Cass Sunstein, collateralized debt obligation, complexity theory, corporate governance, corporate raider, Credit Default Swap, credit default swaps / collateralized debt obligations, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, discovery of the americas, diversification, diversified portfolio, Edward Glaeser, Edward Thorp, endowment effect, Eugene Fama: efficient market hypothesis, experimental economics, financial innovation, Financial Instability Hypothesis, fixed income, floating exchange rates, George Akerlof, Henri Poincaré, Hyman Minsky, implied volatility, impulse control, index arbitrage, index card, index fund, information asymmetry, invisible hand, Isaac Newton, John Meriwether, John Nash: game theory, John von Neumann, joint-stock company, Joseph Schumpeter, Kenneth Arrow, libertarian paternalism, linear programming, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, market bubble, market design, Myron Scholes, New Journalism, Nikolai Kondratiev, Paul Lévy, Paul Samuelson, pension reform, performance metric, Ponzi scheme, prediction markets, pushing on a string, quantitative trading / quantitative finance, Ralph Nader, RAND corporation, random walk, Richard Thaler, risk/return, road to serfdom, Robert Bork, Robert Shiller, Robert Shiller, rolodex, Ronald Reagan, shareholder value, Sharpe ratio, short selling, side project, Silicon Valley, Social Responsibility of Business Is to Increase Its Profits, South Sea Bubble, statistical model, stocks for the long run, The Chicago School, The Myth of the Rational Market, The Predators' Ball, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas L Friedman, Thorstein Veblen, Tobin tax, transaction costs, tulip mania, value at risk, Vanguard fund, Vilfredo Pareto, volatility smile, Yogi Berra

Barber, “Irving Fisher (1867–1947): Career Highlights and Formative Influences,” in Hans-E. Loef and Hans G. Monissen, The Economics of Irving Fisher: Reviewing the Scientific Work of a Great Economist (Cheltenham, UK, Northampton, Mass.: Edward Elgar, 1999), 6. 5. E. Roy Weintraub, “On the Existence of Competitive Equilibrium: 1930–1954,” Journal of Economic Literature (March 1983): 13. 6. It was left to others, such as John Nash of A Beautiful Mind fame, to develop a multiplayer theory of games better suited to modeling economic interactions. 7. John von Neumann and Oskar Morgenstern, Theory of Games and Economic Behavior, 65th Anniversary Edition (Princeton: Princeton University Press, 2004), 177–78. 8. Daniel Bernoulli, “Exposition of a New Theory on the Measurement of Risk,” Econometrica (Jan. 1954): 23–36. 9. The story is Herbert Simon’s: In the early 1950s, when I was on a faculty recruiting trip from Pittsburgh, I had dinner with Marschak one evening in the Quadrangle Club at the University of Chicago.

The result was the 641-page Theory of Games and Economic Behavior, coauthored by von Neumann and Morgenstern and published in 1944. As far as pure game theory went, the book added little to what von Neumann had written in 1928,6 although it gave form and heft to von Neumann’s big idea. It also solved the quandary faced by poor Sherlock Holmes and Dr. Moriarty. According to von Neumann’s calculations, Holmes should choose randomly with a 60 percent probability of getting off at the intermediate station, while Moriarty should pick with a 60 percent probability of proceeding straight to Dover.7 Got that? For economists, the part of the book that made the biggest immediate impression was not game theory itself but the chapter outlining how one should weigh potential outcomes before deciding on a move. The gist of it: When outcomes are uncertain, think probabilistically.

After a brief and spectacularly eventful career as a teenaged social-democratic politician during the years immediately following the Russian Revolution, Marschak fled to Germany, where he studied economics and met von Neumann. At Cowles, he gathered around him a spectacular assemblage of future Nobel winners (“I pick people with good eyes,” he explained9) who together explored the cutting edge of mathematical economics. Von Neumann and Morgenstern’s book was on that cutting edge, and Marschak brought von Neumann to Chicago for a two-day seminar on game theory in 1945. Soon afterward, he wrote an article translating von Neumann and Morgenstern’s concept of expected utility into language that would be understood by his fellow economists. “To be an ‘economic man,’” Marschak summed up, “implies being a ‘statistical man.’”10 IF EVER THERE WAS A statistical man, it was Harry Markowitz. A grocer’s son from northwest Chicago, he sped through a special two-year undergraduate program at the University of Chicago and was pursuing a Ph.D. as a “student member” of the Cowles Commission.


Adam Smith: Father of Economics by Jesse Norman

"Robert Solow", active measures, Andrei Shleifer, balance sheet recession, bank run, banking crisis, Basel III, Berlin Wall, Black Swan, Branko Milanovic, Bretton Woods, British Empire, Broken windows theory, business cycle, business process, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, centre right, cognitive dissonance, collateralized debt obligation, colonial exploitation, Corn Laws, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, David Brooks, David Ricardo: comparative advantage, deindustrialization, Eugene Fama: efficient market hypothesis, experimental economics, Fall of the Berlin Wall, Fellow of the Royal Society, financial intermediation, frictionless, frictionless market, future of work, George Akerlof, Hyman Minsky, income inequality, incomplete markets, information asymmetry, intangible asset, invention of the telescope, invisible hand, Isaac Newton, Jean Tirole, John Nash: game theory, joint-stock company, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, lateral thinking, loss aversion, market bubble, market fundamentalism, Martin Wolf, means of production, money market fund, Mont Pelerin Society, moral hazard, moral panic, Naomi Klein, negative equity, Network effects, new economy, non-tariff barriers, Northern Rock, Pareto efficiency, Paul Samuelson, Peter Thiel, Philip Mirowski, price mechanism, principal–agent problem, profit maximization, purchasing power parity, random walk, rent-seeking, Richard Thaler, Robert Shiller, Robert Shiller, Ronald Coase, scientific worldview, seigniorage, Socratic dialogue, South Sea Bubble, special economic zone, speech recognition, Steven Pinker, The Chicago School, The Myth of the Rational Market, The Nature of the Firm, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Thomas Malthus, Thorstein Veblen, time value of money, transaction costs, transfer pricing, Veblen good, Vilfredo Pareto, Washington Consensus, working poor, zero-sum game

The ingenuity of Edgeworth’s approach was that it plausibly related much more realistic descriptions of how people actually bargain to the mathematically idealized outcomes of perfect competition—it was in this sense more Smithian than Walrasian. Ignored for decades, his ideas were rediscovered and reinvigorated with the work of John Nash and others in the second half of the twentieth century, when they gave rise to important work in the theory of cooperative and non-cooperative games. Game theory was yet another example of mathematics being incorporated into economics. But the core concept of man as a rational economic agent, homo economicus, lay at the centre of all this work; and as economics grew more mathematical, so the idea of homo economicus became progressively narrower. Classical political economists such as John Stuart Mill had thought in terms of general rules, to which numerous exceptions might exist; indeed, exceptions might exist even to the basic principle of free trade itself.

It provides a psychologically plausible account of a core norm of fairness, of ‘putting oneself in another’s shoes’ and seeing things from their perspective—the kind of norm that underlies, for example, the well-known theory of justice developed by the philosopher John Rawls. Overall, the use of game theory enables the idea of norms to be integrated into the equilibrium models beloved of economists. But this is also its weakness, for as a purely formal treatment it operates at a single moment or repeated succession of moments in time. It thus misses the continuous, energetic and ever-changing understanding of human interaction to be found in Smith. As game theory reminds us, far from being irrelevant or subordinate to economics and commercial activity, norms bear directly upon them. Take the issue of how to raise economic productivity, a problem that has bedevilled Western economies in recent decades, and especially since the 2008 crash.

These include the work of Frans de Waal and others on norms of reciprocity in primates; of Joe Henrich and others on the evolutionary selection of social norms in different populations; and of Giacomo Rizzolatti and others on the activity of ‘mirror neurons’—neurons that fire both when a monkey or human performs an action and when they see another monkey or human doing a similar action. Some people have seen a potential grounding in neuroscience for Smith’s idea of ‘sympathy’. Perhaps most striking of all is the degree to which game theory has developed and illuminated ideas to be found in Hume and Smith. From this perspective, norms are a central mechanism by which people come to coordinated solutions to social problems. These solutions can often be formally modelled as ‘Nash equilibria’—that is, as stable states of affairs in which each participant knows the strategies of the others and cannot improve their own strategy as a result.


pages: 402 words: 110,972

Nerds on Wall Street: Math, Machines and Wired Markets by David J. Leinweber

AI winter, algorithmic trading, asset allocation, banking crisis, barriers to entry, Big bang: deregulation of the City of London, business cycle, butter production in bangladesh, butterfly effect, buttonwood tree, buy and hold, buy low sell high, capital asset pricing model, citizen journalism, collateralized debt obligation, corporate governance, Craig Reynolds: boids flock, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, Danny Hillis, demand response, disintermediation, distributed generation, diversification, diversified portfolio, Emanuel Derman, en.wikipedia.org, experimental economics, financial innovation, fixed income, Gordon Gekko, implied volatility, index arbitrage, index fund, information retrieval, intangible asset, Internet Archive, John Nash: game theory, Kenneth Arrow, load shedding, Long Term Capital Management, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, market fragmentation, market microstructure, Mars Rover, Metcalfe’s law, moral hazard, mutually assured destruction, Myron Scholes, natural language processing, negative equity, Network effects, optical character recognition, paper trading, passive investing, pez dispenser, phenotype, prediction markets, quantitative hedge fund, quantitative trading / quantitative finance, QWERTY keyboard, RAND corporation, random walk, Ray Kurzweil, Renaissance Technologies, risk tolerance, risk-adjusted returns, risk/return, Robert Metcalfe, Ronald Reagan, Rubik’s Cube, semantic web, Sharpe ratio, short selling, Silicon Valley, Small Order Execution System, smart grid, smart meter, social web, South Sea Bubble, statistical arbitrage, statistical model, Steve Jobs, Steven Levy, Tacoma Narrows Bridge, the scientific method, The Wisdom of Crowds, time value of money, too big to fail, transaction costs, Turing machine, Upton Sinclair, value at risk, Vernor Vinge, yield curve, Yogi Berra, your tax dollars at work

It depends how fast your information decays, and how willing you are to gamble that it will be known before you finish trading. Source: Robert Almgren and Neil Chriss, “Optimal Execution of Portfolio Transactions,” Journal of Risk 3, no. 2 (Winter 2000/2001). 10 Share Holdings 8 C B 6 4 A 2 0 0 1 2 3 Time Periods 77 4 5 Mathematical models of markets can become very elaborate. Game theoretic approaches to other market participants, human and machine, in the spirit of the Beautiful Mind ideas of John Nash, bring another level of insight. Known Unknowns and Unknown Unknowns Almgren and Chriss close with an important point about the limitations of all model-driven strategies. As part of the Algos 201 track, here is what they say about connecting algorithms to real-world events: Finally, we note that any optimal execution strategy is vulnerable to unanticipated events. If such an event occurs during the course of trading and causes a material shift in the parameters of the price dynamics, then indeed a shift in the optimal trading strategy must also occur.

I was blissfully unaware that I was passing through the same hallways used by some of the seminal thinkers of modern finance and economics: William Sharpe, Harry Markowitz, Kenneth Arrow, and George Dantzig. Markowitz and Sharpe, in particular, pioneered the ideas of balancing risk and reward in a systematic way, which when applied to finance, eventually led to their sharing the Nobel Prize in 1990. To digress just a bit, RAND’s interest in systematically approaching risk and reward, optimization, decision under uncertainty, and game theory was not initially conceived in the context of finance. RAND was motivated by the challenges of World War II and the Cold War.Think of the types of problems faced by the Army Air Corps, predecessor of the modern U.S. Air Force, in World War I. Military aviation involved flying small planes to take a look at the situation on the ground, occasionally encountering someone doing the same thing for the other side.


One Bullet Away: The Making of a Marine Officer by Fick, Nathaniel C.(October 3, 2005) Hardcover by Nathaniel C. Fick

clean water, defense in depth, double helix, friendly fire, John Nash: game theory, Khyber Pass, Silicon Valley

A portion of this book’s proceeds will be donated to veterans’ organizations, including the Marine Corps Scholarship Foundation, dedicated to funding higher education for the children of Marines killed in action. I thank my parents, Niel and Jane, and my sisters, Maureen and Stephanie, for their boundless love and support. In worrying, mailing cookies, and listening, they also served. My fellow platoon commanders were, and are, comrades in the truest sense. Thank you to Patrick English, Vijay George, Ed Hinman, Ty Moore, Walt Messick, Brendan Sullivan, John Nash, and Jim Beal. My former commanding officer Rich Whitmer taught me more than he will ever acknowledge. Thank you, Oden Six. To Keith Marine, I can only say “Dang.” I am forever grateful to Mike Wynn, Brad Colbert, Shawn Patrick, Rudy Reyes, Steve Lovell, Tony Espera, Tim Bryan, Mike Stinetorf, Hector Leon, Gabe Garza, Evan Stafford, Anthony “Manimal” Jacks, Walt Hasser, Nathan Christopher, James Chaffin, Harold Trombley, Teren “T” Holsey, John Christeson, Michael Brunmeier, Jason Lilley, Josh Person, Leandro “Shady” Baptista, Eric Kocher, Dan Redman, and A.

We used METT-T to estimate a tactical situation in order to complete the plan: mission, enemy, terrain, troops and fire support available, time. Most of all, we began to issue orders. Not yelled commands in mid-assault, but multipage written orders built around the five-paragraph format called SMEAC: situation, mission, execution, administration and logistics, command and signal. We wrote dozens of them. Instruction at TBS goes far beyond rote memorization, growing into some amalgamation of chess, history, boxing, and game theory. We studied the fog and friction of war, how the simplest things become difficult. During our written test on the subject, the instructors cranked Metallica at full volume, hurled tennis balls at our heads, and sprayed our faces with water pistols. The lesson was focus: ignore the distractions and do your job. We learned about warfare’s dynamism. We wouldn’t be fighting wax men in castles. In our instructors’ words, “The enemy has a vote, too.”


pages: 505 words: 142,118

A Man for All Markets by Edward O. Thorp

3Com Palm IPO, Albert Einstein, asset allocation, beat the dealer, Bernie Madoff, Black Swan, Black-Scholes formula, Brownian motion, buy and hold, buy low sell high, carried interest, Chuck Templeton: OpenTable:, Claude Shannon: information theory, cognitive dissonance, collateralized debt obligation, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, Edward Thorp, Erdős number, Eugene Fama: efficient market hypothesis, financial innovation, George Santayana, German hyperinflation, Henri Poincaré, high net worth, High speed trading, index arbitrage, index fund, interest rate swap, invisible hand, Jarndyce and Jarndyce, Jeff Bezos, John Meriwether, John Nash: game theory, Kenneth Arrow, Livingstone, I presume, Long Term Capital Management, Louis Bachelier, margin call, Mason jar, merger arbitrage, Murray Gell-Mann, Myron Scholes, NetJets, Norbert Wiener, passive investing, Paul Erdős, Paul Samuelson, Pluto: dwarf planet, Ponzi scheme, price anchoring, publish or perish, quantitative trading / quantitative finance, race to the bottom, random walk, Renaissance Technologies, RFID, Richard Feynman, risk-adjusted returns, Robert Shiller, Robert Shiller, rolodex, Sharpe ratio, short selling, Silicon Valley, Stanford marshmallow experiment, statistical arbitrage, stem cell, stocks for the long run, survivorship bias, The Myth of the Rational Market, The Predators' Ball, the rule of 72, The Wisdom of Crowds, too big to fail, Upton Sinclair, value at risk, Vanguard fund, Vilfredo Pareto, Works Progress Administration

MIT had become one of the world’s great mathematics centers, following its transformation by projects for the government during World War II from a technical school to a scientific powerhouse. Simply walking down the hall, I would chat with people like the prodigy Professor Norbert Wiener (cybernetics) and the future Abel Prize winner Isadore Singer. The C. L. E. Moore Instructorship program, of which I was part, had brought in new PhDs like John Nash, who later won the Nobel for economics, and future Fields Medal winner Paul Cohen. Though there’s no Nobel Prize for mathematics, the Fields and the Abel prizes have that status. Cohen had left a few days before I arrived; his name was just being scraped off his door. I finally decided not to stay on. From a career standpoint, I thought I had the talent to keep up with the big boys but I felt I needed more mathematical background.

Kassouf) helped start the derivatives revolution that transformed world securities markets. Based on his work, he launched the first market-neutral hedge fund in 1969. Dr. Thorp, with Claude Shannon, also invented the first wearable computer in 1961 to win at roulette. He has also written Elementary Probability (1966), The Mathematics of Gambling (1984), and numerous mathematical papers on probability, game theory, and functional analysis. He completed undergraduate and graduate work at UCLA, receiving the BA and MA in physics, and the PhD in mathematics in 1958. He has taught at UCLA, MIT, and New Mexico State University, and was Professor of Mathematics and Finance at the University of California, Irvine. edwardothorp.com amanforallmarkets.com What’s next on your reading list? Discover your next great read!


pages: 604 words: 161,455

The Moral Animal: Evolutionary Psychology and Everyday Life by Robert Wright

"Robert Solow", agricultural Revolution, Andrei Shleifer, Asian financial crisis, British Empire, centre right, cognitive dissonance, double entry bookkeeping, double helix, fault tolerance, Francis Fukuyama: the end of history, George Gilder, global village, invention of gunpowder, invention of movable type, invention of the telegraph, invention of writing, invisible hand, John Nash: game theory, John von Neumann, Marshall McLuhan, Norbert Wiener, planetary scale, pre–internet, profit motive, Ralph Waldo Emerson, random walk, Richard Thaler, rising living standards, Silicon Valley, social intelligence, social web, Steven Pinker, talking drums, the medium is the message, The Wealth of Nations by Adam Smith, trade route, your tax dollars at work, zero-sum game

Imagine: college students turning down real money for no work! Apparently there are some kinds of non-zero-sum games that people just won’t play.† And this pride is found cross culturally; experiments in Japan, Slovenia, the United States, and Israel yield the same basic results. To say that people naturally resist extremely raw deals isn’t, of course, to say that raw deals don’t happen. In 1994, the game theorist John Nash won the Nobel Prize for, among other things, rigorously exploring how various circumstances could weaken one’s bargaining position, so that “logical” outcomes of non-zero-sum games may not be what most of us would call fair. Thus, when people of different income levels bargain over how to divide the benefits of their joint and equal labors, the richer person is in a stronger position; the player who needs the money less can more credibly threaten to drop out of the game altogether.† In chiefdoms, the commoners’ bargaining disadvantage went beyond their low incomes.

“There’s something about the ‘umness’ part,” one of them said. So I backed down. But I did liberally pepper the book with the term—and with such allied terms as “non-zero-sum” and “negative sum,” and so on. What’s more, I did title the book “Nonzero.” Why am I so attached to the terminology of game theory? Does it really add anything to more familiar words? Can’t we just say, for example, that zero-sum games are competitive and non-zero-sum games are cooperative? There are several reasons that I think the answer is no—that there’s no substitute for game theory as a way of looking at the history of our species. For starters, there are a number of cases in which people comply with non-zero-sum logic, and yet “cooperate” is a misleading word. I have a non-zero-sum relationship with the people in Japan who built my Honda minivan, but neither I nor they ever chose to cooperate with each other.

Part of the argument of this book is that the logic of biological integration and of social integration can be subsumed in a single analytical framework. And it seemed to me that, if I wanted a vocabulary that would apply not just to people, but to genes, then it was better to minimize the use of fuzzy terms like “cooperate” and stick mainly with cold, precise terms such as “non-zero-sum.” (A particular appeal of using game theory in biology is that in Darwinian theory the “payoff” is clearly and quantitatively defined—as genetic proliferation; so actually adding up the nonzero sums is in theory doable without making artificial assumptions.) The terminology of game theory helps unify not just human history and organic history. Within each of these realms, the terminology can be unifying. If you ask what is common to reciprocal altruism and kin selection (two basic biological routes to social integration), the answer is non-zero-sum logic.


pages: 467 words: 154,960

Trend Following: How Great Traders Make Millions in Up or Down Markets by Michael W. Covel

Albert Einstein, Atul Gawande, backtesting, beat the dealer, Bernie Madoff, Black Swan, buy and hold, buy low sell high, capital asset pricing model, Clayton Christensen, commodity trading advisor, computerized trading, correlation coefficient, Daniel Kahneman / Amos Tversky, delayed gratification, deliberate practice, diversification, diversified portfolio, Edward Thorp, Elliott wave, Emanuel Derman, Eugene Fama: efficient market hypothesis, Everything should be made as simple as possible, fiat currency, fixed income, game design, hindsight bias, housing crisis, index fund, Isaac Newton, John Meriwether, John Nash: game theory, linear programming, Long Term Capital Management, mandelbrot fractal, margin call, market bubble, market fundamentalism, market microstructure, mental accounting, money market fund, Myron Scholes, Nash equilibrium, new economy, Nick Leeson, Ponzi scheme, prediction markets, random walk, Renaissance Technologies, Richard Feynman, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, Robert Shiller, shareholder value, Sharpe ratio, short selling, South Sea Bubble, Stephen Hawking, survivorship bias, systematic trading, the scientific method, Thomas L Friedman, too big to fail, transaction costs, upwardly mobile, value at risk, Vanguard fund, William of Occam, zero-sum game

Now, suppose the payoff was changed to 3/2, a gain of $1.50 in addition to a $1 bet—the expectation would change to: (.5) (1.5) + (.5) (–1) = +.25 Playing this game 100 times would give us a positive expectation of .25.8 This is the kind of edge cultivated and honed daily by trend followers. You might ask, “If everyone knows about expectation, how can I ever find my edge?” Think about it this way. Consider a scene from the movie A Beautiful Mind, the biography of mathematician John Nash. Nash and some of his mathematician buddies are in a bar when a sexy blonde and four brunettes walk in. After they admire the new arrivals, Nash and his friends decide to compete for the blonde. However, Nash has reservations, correctly observing that, if everyone goes for the same woman, they will just end up blocking each other out. Worse, they will offend the rest of the women. The Volatility, risk, and profit are closely related.

Traders pay close attention to volatility because price changes affect their profits and losses. Periods of high volatility are highly risky to traders. Such periods, however, can also present them with opportunities for great profits.9 252 Trend Following (Updated Edition): Learn to Make Millions in Up or Down Markets only way for everyone to succeed is to ignore the blonde and hit on the brunettes. The scene dramatizes the Nash Equilibrium, his most important contribution to game theory. Nash proved that in any competitive situation—war, chess, even picking up a date at a bar—if the participants are rational and they know that their opponents are rational, there is only one optimal strategy. That theory won Nash a Nobel Prize in economics and transformed the way we think about competition in both games and the real world.10 Building off Nash’s general thoughts, Ed Seykota lays out a basic risk definition from a trading perspective: “Risk is the possibility of loss.”

, 273-274 fashion metaphor, 50 fat tails, 228 Faulkner, Charles, 3, 15, 21, 28, 33, 66, 193-194, 197-198, 201-203, 206-208, 214, 223, 253, 282, 299-302 Fawcett, George, 273 Federal Reserve announcements, reaction to, 56-57 Feinstein, Diane, 146 Feynman, Richard, 16 “fight-or-flight” mode, 197 First Gulf War, 176-178 five-year notes trading, 130 Florida Marlins, 187 Forrester, Jay, 62-63 Fouts, Roger, 209 Franiak, Frank J., 167 Freud, Sigmund, 206, 221 Friedman, Thomas, 28, 143, 256, 267 FTSE chart (2002), trend-followers and, 141 fundamental analysis, 7-9, 177, 212 Futures and Options Expo, 72 futures exchanges, 3 Futures Magazine, xvi Galilei, Galileo, 68 Galton, Francis, 32 game theory, 251 game, trading as, 277-278 Garcia, Jerry, 243 Gardner, David, 9 Gardner, Tom, 9 Gartman, Dennis, 116 “The Gartman Letter,” 116 Gawande, Atul, 209 generalists, trend followers as, 28 German Bund chart (1998), trend-followers and, 159 Gigerenzer, Gerd, 211, 213-214, 216, 224 Gladwell, Malcolm, 158, 169 Glassman, James, 231-232, 235 gold trading, 129 Goldman Sachs, 153 Goleman, Daniel, 196, 200-201 Good to Great (Collins), xviii, 33 Goodman, Marc, 105 Gould, Stephen Jay, 189 government, market system and, 4 Graham Capital Management, 21, 147 greed and behavioral finance, 196 Greenberg, Alan “Ace”, 205 Griffin, Ken, 111 Griffith, Bill, 18 Gulf War (first), 176-178 Gunther, Max, 283 Hamer, Jim, 66 Harding, David, xv, xx, 29-32, 105, 109, 124, 182, 199, 215, 230, 281, 289, 295 Harris, Larry, 114-115, 278 Harrison, Alfred, 235 “Has Trend Following Changed?”


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The Rational Optimist: How Prosperity Evolves by Matt Ridley

"Robert Solow", 23andMe, agricultural Revolution, air freight, back-to-the-land, banking crisis, barriers to entry, Bernie Madoff, British Empire, call centre, carbon footprint, Cesare Marchetti: Marchetti’s constant, charter city, clean water, cloud computing, cognitive dissonance, collateralized debt obligation, colonial exploitation, colonial rule, Corn Laws, creative destruction, credit crunch, David Ricardo: comparative advantage, decarbonisation, dematerialisation, demographic dividend, demographic transition, double entry bookkeeping, Edward Glaeser, en.wikipedia.org, everywhere but in the productivity statistics, falling living standards, feminist movement, financial innovation, Flynn Effect, food miles, Gordon Gekko, greed is good, Hans Rosling, happiness index / gross national happiness, haute cuisine, hedonic treadmill, Hernando de Soto, income inequality, income per capita, Indoor air pollution, informal economy, Intergovernmental Panel on Climate Change (IPCC), invention of agriculture, invisible hand, James Hargreaves, James Watt: steam engine, Jane Jacobs, John Nash: game theory, joint-stock limited liability company, Joseph Schumpeter, Kevin Kelly, Kickstarter, knowledge worker, Kula ring, Mark Zuckerberg, meta analysis, meta-analysis, mutually assured destruction, Naomi Klein, Northern Rock, nuclear winter, oil shale / tar sands, out of africa, packet switching, patent troll, Pax Mongolica, Peter Thiel, phenotype, plutocrats, Plutocrats, Ponzi scheme, Productivity paradox, profit motive, purchasing power parity, race to the bottom, Ray Kurzweil, rent-seeking, rising living standards, Silicon Valley, spice trade, spinning jenny, stem cell, Steve Jobs, Steven Pinker, Stewart Brand, supervolcano, technological singularity, Thales and the olive presses, Thales of Miletus, The Wealth of Nations by Adam Smith, Thorstein Veblen, trade route, transaction costs, ultimatum game, upwardly mobile, urban sprawl, Vernor Vinge, Vilfredo Pareto, wage slave, working poor, working-age population, Y2K, Yogi Berra, zero-sum game

The Ascent of Money. Allen Lane. p. 85 Homicide rate graph. Spierenburg, P. 2008. A History of Murder. Polity Press. See also Eisner, M. 2001. Modernization, Self-Control and Lethal Violence. The Long-term Dynamics of European Homicide Rates in Theoretical Perspective The British Journal of Criminology 41:618-638. p. 85 ‘Greenstreet whispers to Bogart’. Siegfried, T. 2006. A Beautiful Math: John Nash, Game Theory and the Modern Quest for a Code of Nature. Joseph Henry Press. p. 86 ‘As the economist Herb Gintis puts it’. http://www.reason.com/news/show/34772.html. p. 86 ‘people in fifteen mostly small-scale tribal societies were enticed to play the Ultimatum Game’. Henrich, J. et al. 2005. ‘Economic man’ in crosscultural perspective: Behavioral experiments in 15 small-scale societies. Behavioral and Brain Sciences 28:795–815.


pages: 512 words: 165,704

Traffic: Why We Drive the Way We Do (And What It Says About Us) by Tom Vanderbilt

Albert Einstein, autonomous vehicles, availability heuristic, Berlin Wall, call centre, cellular automata, Cesare Marchetti: Marchetti’s constant, cognitive dissonance, computer vision, congestion charging, Daniel Kahneman / Amos Tversky, DARPA: Urban Challenge, endowment effect, extreme commuting, fundamental attribution error, Google Earth, hedonic treadmill, hindsight bias, hive mind, if you build it, they will come, impulse control, income inequality, Induced demand, invisible hand, Isaac Newton, Jane Jacobs, John Nash: game theory, Kenneth Arrow, lake wobegon effect, loss aversion, megacity, Milgram experiment, Nash equilibrium, Sam Peltzman, Silicon Valley, statistical model, the built environment, The Death and Life of Great American Cities, traffic fines, ultimatum game, urban planning, urban sprawl, women in the workforce, working poor

From the point of view of the individual driver, this behavior makes sense. After all, if the driver gets off the highway and goes to Sure Thing Street, he or she will not save time. The driver will save time only if others get off the highway—but why should they? The drivers are locked into what is called a Nash equilibrium, a strategic concept from the annals of Cold War thinking. Popularized by the Nobel mathematician John Nash, it describes a state in which no one player of an experimental game can make himself better off by his own action alone. If you cannot improve your situation, why move to a different road? The irony is that when everyone does what is best for him- or herself, they’re not doing what is best for everyone. On the other hand, if a traffic cop stood at the junction of the two roads and directed half the drivers to Sure Thing Street and half to Take a Chance Highway, the drivers on Sure Thing Street would get home no sooner, but the highway drivers would get home twice as fast.

Your daily drive may not seem to have much to do with the strategies of the Cold War, but every time two cars approach an unmarked intersection simultaneously, or four cars sidle up to a four-way stop at about the same time, a form of game theory is being applied. Game theory, as defined by the Nobel Prize–winning economist Thomas Schelling, is the process of strategic decision making that occurs when, as in a nuclear standoff or a stop-sign showdown, “two or more individuals have choices to make, preferences regarding the outcomes, and some knowledge of the choices available to each other and of each other’s preferences. The outcome depends on the choices that both of them make, or all of them if there are more than two.” Traffic is filled with these daily moments of impromptu decision making and brinksmanship. As Schelling has argued, one of the most effective, albeit risky, strategies in game theory involves the use of an “asymmetry in communication.” One driver, like Barrios Gómez in Mexico City, makes himself “unavailable” to receive messages, and thus cannot be swayed from going first through the intersection.


pages: 829 words: 186,976

The Signal and the Noise: Why So Many Predictions Fail-But Some Don't by Nate Silver

"Robert Solow", airport security, availability heuristic, Bayesian statistics, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, big-box store, Black Swan, Broken windows theory, business cycle, buy and hold, Carmen Reinhart, Claude Shannon: information theory, Climategate, Climatic Research Unit, cognitive dissonance, collapse of Lehman Brothers, collateralized debt obligation, complexity theory, computer age, correlation does not imply causation, Credit Default Swap, credit default swaps / collateralized debt obligations, cuban missile crisis, Daniel Kahneman / Amos Tversky, diversification, Donald Trump, Edmond Halley, Edward Lorenz: Chaos theory, en.wikipedia.org, equity premium, Eugene Fama: efficient market hypothesis, everywhere but in the productivity statistics, fear of failure, Fellow of the Royal Society, Freestyle chess, fudge factor, George Akerlof, global pandemic, haute cuisine, Henri Poincaré, high batting average, housing crisis, income per capita, index fund, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), Internet Archive, invention of the printing press, invisible hand, Isaac Newton, James Watt: steam engine, John Nash: game theory, John von Neumann, Kenneth Rogoff, knowledge economy, Laplace demon, locking in a profit, Loma Prieta earthquake, market bubble, Mikhail Gorbachev, Moneyball by Michael Lewis explains big data, Monroe Doctrine, mortgage debt, Nate Silver, negative equity, new economy, Norbert Wiener, PageRank, pattern recognition, pets.com, Pierre-Simon Laplace, prediction markets, Productivity paradox, random walk, Richard Thaler, Robert Shiller, Robert Shiller, Rodney Brooks, Ronald Reagan, Saturday Night Live, savings glut, security theater, short selling, Skype, statistical model, Steven Pinker, The Great Moderation, The Market for Lemons, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, too big to fail, transaction costs, transfer pricing, University of East Anglia, Watson beat the top human players on Jeopardy!, wikimedia commons

We may focus on those signals which advance our preferred theory about the world, or might imply a more optimistic outcome. Or we may simply focus on the ones that fit with bureaucratic protocol, like the doctrine that sabotage rather than an air attack was the more likely threat to Pearl Harbor. The Unfamiliar and the Improbable Rumsfeld’s favorite part of Wohlstetter’s book is the foreword, composed by the Nobel Prize–winning economist Thomas Schelling, who was instrumental in translating John Nash’s early work on game theory into national-security contexts. Schelling writes of our propensity to mistake the unfamiliar for the improbable: There is a tendency in our planning to confuse the unfamiliar with the improbable. The contingency we have not considered seriously looks strange; what looks strange is thought improbable; what is improbable need not be considered seriously. Because of the United States’ isolation from the European and Asian continents and the relatively good relations we have maintained with the rest of the Americas since the promulgation of the Monroe Doctrine, we have infrequently been the subject of foreign attack.

At the same time, the system was designed to be slightly biased toward complicated positions, which played more to its strengths. “Positions that are good for computers are complex positions with lots of pieces on the board so there’s lots of legal moves available,” Campbell told me. “We want the positions where tactics are more important than strategy. So you can do some minor things to encourage that.” In this sense, Deep Blue was more “human” than any chess computer before or since. Although game theory does not come into play in chess to the same degree it does in games of incomplete information like poker, the opening sequences are one potential exception. Making a slightly inferior move to throw your opponent off-balance can undermine months of his preparation time—or months of yours if he knows the right response to it. But most computers try to play “perfect” chess rather than varying their game to match up well against their opponent.

., 5, 149 progress and, 5 updating of, 73 forecasting, global warming, 380–82 complexity in, 382 consensus in, 382–84 uncertainty in, 382 ForecastWatch.com, 132 foreshocks, 144, 154, 155–57, 476 Fort Dix, 204, 206, 208, 223–25, 229 Fort Riley, 205 fortune-telling, 5 Fourier, Joseph, 375 foxes, 53–54, 54, 55, 73 consensus process emulated by, 67 improvements in predictions by, 57, 68 as television pundits, 56 Fox News, 51n, 55, 56 France, 120 Franklin, Benjamin, 262 Freakonomics (Levitt and Dubner), 9 Freakonomics blog, 136–37, 334 FRED, 225–26 Freddie Mac, 33 free agents, 82, 90, 94, 99 free markets, 1, 128, 332, 369, 370, 451, 496–97 free will, 112 see also determinism French Wars of Religion, 4 frequentism, 252–53, 254, 259, 260 Freud, Sigmund, 53 Friedel, Frederic, 278–79, 282–83 Fritz, 278, 282n Frontline, 370n Fukushima nuclear reactor, 11, 168 Full Tilt Poker, 309 fundamental analysis, 341, 348, 354 fundamentals-based models, in elections forecasting, 68 futarchy, 201 Future Shock (Toffler), 12, 13 Galfond, Phil, 309 Galileo, 4, 254 Gallup polls, 364–65, 497 gambling, 232–61, 238 on baseball, 286 Bayesian philosophy’s esteem for, 255–56, 362 over-under line, 239–40, 257, 286 point spread, 239 Game Change, 59 Game of the Century, 286–88, 287 game theory, 284–85, 311, 419 Gates, Bill, 264 Gates, H. L. “Skip,” 417n GDP, 482 forecasting of, 180, 181–83, 182, 186n, 190, 194, 198, 199, 200–201, 202–3 growth in, vs. job growth, 189 Gehringer, Charlie, 84, 85 German Peasants’ War, 4 Germany, 2, 115, 120, 210 Germany, East, 52 Giambi, Jason, 99 GIGO (garbage in, garbage out), 289 GISS temperature record, 393–95 Giuliani, Giampaolo, 143, 144–45, 146, 476 Gladwell, Malcolm, 53 global cooling, 399–400 global financial crisis, 11, 16, 20, 30–36, 39–43, 118–19, 329 failure to predict, 181, 327 global population, growth of, 212 global warming, 13 causality and, 372–73 Climategate and, 408 contrarianism and, 380 Copenhagen conference on, 378–80 IPCC report on, see International Panel on Climate Change (IPCC) predictions of, 373–76, 393, 397–99, 401–6, 402, 507 self-interest and, 380 skepticism of, 377, 380, 383, 384–85 use of term, 376, 377n Goldman Sachs, 24n, 184–85, 199, 364 gonorrhea, 222 Goodhart’s law, 188 Google, 264, 290–92 creative culture at, 291 Google searches, 200, 290–91 Gorbachev, Mikhail, 50, 51, 52, 160 Gore, Al, 11, 67, 68, 381–82, 381, 385, 403, 514, 469 government spending, 42, 186n GPS, 174–75, 219 Graham, Benjamin, 364 Grand Forks, N.


pages: 1,073 words: 314,528

Strategy: A History by Lawrence Freedman

Albert Einstein, anti-communist, Anton Chekhov, Ayatollah Khomeini, barriers to entry, battle of ideas, Black Swan, British Empire, business process, butterfly effect, centre right, Charles Lindbergh, circulation of elites, cognitive dissonance, coherent worldview, collective bargaining, complexity theory, conceptual framework, corporate raider, correlation does not imply causation, creative destruction, cuban missile crisis, Daniel Kahneman / Amos Tversky, defense in depth, desegregation, Edward Lorenz: Chaos theory, en.wikipedia.org, endogenous growth, endowment effect, Ford paid five dollars a day, framing effect, Frederick Winslow Taylor, Gordon Gekko, greed is good, information retrieval, interchangeable parts, invisible hand, John Nash: game theory, John von Neumann, Kenneth Arrow, lateral thinking, linear programming, loose coupling, loss aversion, Mahatma Gandhi, means of production, mental accounting, Murray Gell-Mann, mutually assured destruction, Nash equilibrium, Nelson Mandela, Norbert Wiener, Norman Mailer, oil shock, Pareto efficiency, performance metric, Philip Mirowski, prisoner's dilemma, profit maximization, race to the bottom, Ralph Nader, RAND corporation, Richard Thaler, road to serfdom, Ronald Reagan, Rosa Parks, shareholder value, social intelligence, Steven Pinker, strikebreaker, The Chicago School, The Myth of the Rational Market, the scientific method, theory of mind, Thomas Davenport, Thomas Kuhn: the structure of scientific revolutions, Torches of Freedom, Toyota Production System, transaction costs, ultimatum game, unemployed young men, Upton Sinclair, urban sprawl, Vilfredo Pareto, War on Poverty, women in the workforce, Yogi Berra, zero-sum game

In their landmark book of 1957, which gave the field renewed vigor, Duncan Luce and Howard Raiffa noted prematurely the decline of the “naive bandwagon-feeling that game theory solved innumerable problems of sociology and economics, or at the least, that it made their solution a practical matter of a few years’ work.”2 They urged social scientists to recognize that game theory was not descriptive. Instead it was “rather (conditionally) normative. It states neither how people do behave nor how they should behave in an absolute sense, but how they should behave if they wish to achieve certain ends.”3 Their injunction was ignored and game theory came to be adopted as more of a descriptive than normative tool. One reason for this was the development of the Nash equilibrium, named after the mathematician John Nash (whose struggle with mental illness became the subject of a book and a movie).4 This was an approach to nonzero-sum games.

In a 1949 article, Brodie referred to game theory in a footnote as a source of “mathematical systematization,” adding that “for various reasons” he did not share the authors’ “conviction that their theory could be directly and profitably applied to problems of military strategy.”15 Later, while finding its “refinements” of little use, he acknowledged the value of the “constant reminder that in war we shall be dealing with an opponent who will react to our moves and to whom we must react.”16 Few of the books on nuclear strategy made much, if any, mention of game theory. This absence was notable in a book by one of the founders of game theory, Oskar Morgenstern.17 Bruce-Briggs suggests that the close association between nuclear strategy and game theory was a consequence of the reception of Kahn’s On Thermonuclear War. Although Kahn had used neither game theory nor mathematics, he was accused of being the most extreme example of a game-theory-wielding militarist, a moniker implying great technical capacity but no moral sensibility. Schelling was also included in this category.18 Schelling observed at the time, “I don’t see that game theory is any more involved than Latin grammar or geophysics; but its quaint name makes mysterious and patronizing references to it an effective ploy.”19 Schelling had little background in military issues.

He shared the view, growing among the operational research community, that advanced mathematics and abstract models were making their work less accessible to potential users,12 and he always opposed the suggestion that strategy was or should be “a branch of mathematics.”13 He confessed to having learned more “from reading ancient Greek history and by looking at salesmanship than studying game theory.” The greatest achievement of game theory, as far as he was concerned, was the payoff matrix. It was extraordinarily useful to be able to put together in a matrix a “simple situation involving as few as two people and two choices.”14 His equivocation on game theory was not unique. Other nuclear strategists who worked at RAND during the 1950s tended to talk of following the “spirit” of game theory rather than its rules. In a 1949 article, Brodie referred to game theory in a footnote as a source of “mathematical systematization,” adding that “for various reasons” he did not share the authors’ “conviction that their theory could be directly and profitably applied to problems of military strategy.”15 Later, while finding its “refinements” of little use, he acknowledged the value of the “constant reminder that in war we shall be dealing with an opponent who will react to our moves and to whom we must react.”16 Few of the books on nuclear strategy made much, if any, mention of game theory.