306:, Young provides a clear and compact exposition of the major results in the field of stochastic evolutionary game theory, which he pioneered. He introduces his model of social interactions called 'adaptive play.' Agents are randomly selected from a large population to play a fixed game. They choose a myopic best response, based upon a random sample of past plays of the game. The evolution of the (bounded) history of play is described by a finite Markov chain. Idiosyncratic behavior or mistakes constantly perturb the process, so that every state is accessible from every other. This means that the Markov chain is ergodic, so there is a unique stationary distribution which characterizes the long-run behavior of the process. Recent work by Young and coauthors finds that evolutionary dynamics of this and other kinds can transit rapidly to stochastically stable equilibria from locally stable ones, when perturbations are small but nonvanishing (Arieli and Young 2016, Kreindler and Young 2013, Kreindler and Young 2014).
299:: "The stochastically stable set is the set of states such that, in the long run, it is nearly certain that the system lies within every open set containing S as the noise tends slowly to zero" . This solution concept created a major impact in economics and game theory after Young (1993) developed a more tractable version of the theory for general finite-state Markov chains. A state is stochastically stable if it attracts positive weight in the stationary distribution of the Markov chain. Young develops powerful graph-theoretic tools for identifying the stochastically stable states.
330:. Young has made numerous contributions to this literature. Foster and Young (2001) demonstrate the failure of Bayesian learning rules to learn mixed equilibria in games of uncertain information. Foster and Young (2003) introduce a learning procedure in which players form hypotheses about their opponents' strategies, which they occasionally test against their opponents' past play. By backing off from rationality in this way, Foster and Young show that there are natural and robust learning procedures that lead to Nash equilibrium in general normal form games.
378:
was considerable compression in the contract terms: 98% of all contracts involved 1/2-1/2, 2/5-3/5 or 1/3-2/3 splits. Secondly, when splitting the sample into farms from
Northern and Southern Illinois, Young and Burke discovered a high degree of uniformity in contracts within each region, but significant variance across regions---evidence of the local conformity/global diversity effect. In Northern Illinois, the customary share was 1/2-1/2. In Southern Illinois, it was 1/3-2/3 or 2/5-3/5.
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prefers to be segregated. In addition, the theory "demonstrates how high-rationality solution concepts in game theory can emerge in a world populated by low-rationality agents" . In bargaining games, Young demonstrates that the Nash (1950) and Kalai-Smorodinsky (1975) bargaining solutions emerge from the decentralized actions of boundedly rational agents without common knowledge.
374:: A norm is one of many possible equilibria. Compression implies that individuals who are closely connected conform fairly closely to a particular norm. At the same time, the presence of multiple equilibria implies that less closely connected individuals in the population could arrive at a very different norm.
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Young has also made significant applied contributions to understanding the diffusion of new ideas, technologies and practices in a population. The spread of particular social norms can be analyzed within the same framework. In the course of several papers (Young 2003, Young 2011, Kreindler and Young
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These predictions are borne out in empirical work. Several regularities were uncovered in Young and Burke's (2001) study of cropsharing contracts in
Illinois, which made use of detailed information on the terms of contracts on several thousand farms from different parts of the state. Firstly, there
309:
The theory is used to show that in 2x2 coordination games, the risk-dominant equilibrium will be played virtually all the time, as time goes to infinity. It also yields a formal proof of Thomas
Schelling's (1971) result that residential segregation emerges at the social level even if no individual
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concept, identify states from which small once-off deviations are self-correcting. These stability concepts are not appropriate for analyzing social and economic systems which are constantly perturbed by idiosyncratic behavior and mistakes, and individual and aggregate shocks to payoffs. Building
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in 2018. He served as president of the Game Theory
Society from 2006–08. He has published widely on learning in games, the evolution of social norms and institutions, cooperative game theory, bargaining and negotiation, taxation and cost allocation, political representation, voting procedures, and
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as assistant professor and then associate professor, from 1971 to 1976. From 1976 to 1982, Young was research scholar and deputy chairman of the
Systems and Decision Sciences Division at the Institute for Applied Systems Analysis, Austria. He was then appointed professor of Economics and Public
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Young characterized the mean dynamic of each of these processes under general forms of heterogeneity in individual beliefs and preferences. While each of the dynamics yields a familiar S-shaped adoption curve, Young showed how the underlying adoption process can be inferred from the aggregate
436:. Consequently, the Shapley value is the only efficient and symmetric solution that satisfies monotonicity which requires that whenever a player's contribution to all coalitions weakly increases, then this player's allocation should also weakly increase. This justifies the Shapley value as
432:. It is regarded as a key piece for understanding the relationship between the marginality principle and the Shapley value. Young shows that the Shapley value is the only symmetric and efficient solution concept that is solely computed from a player's marginal contributions in a
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adoption curve. It turns out that each process leaves a distinct footprint. Turning to data on hybrid corn adoption in the United States, Young presented evidence of superexponential acceleration in the early stages of adoption, a hallmark of social learning.
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The third adoption process is most closely related to optimizing behavior and thus standard approaches in economics. The first two processes are, however, the ones focused on by the vast sociological and marketing literature on the subject.
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In an influential 2009 paper, Young turned attention to the diffusion dynamics that can result from different adoption rules in a well-mixed population. In particular, he distinguished between three different classes of diffusion model:
360:: when norms change, they do so suddenly. Deviations from an established norm may occur incrementally at first. Once a critical mass of deviators forms, however, the process tips and a new norm spreads rapidly through the population.
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In a series of papers, Young has applied the techniques of stochastic evolutionary game theory to the study of social norms (see Young 2015 for a review). The theory identifies four key features of norm dynamics.
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in 1959. Young and
Levenglick (1978) showed that this method was the unique neutral method satisfying reinforcement and the Condorcet criterion. In other papers (Young 1986, 1988, 1995, 1997), Young adopted an
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approach to preference-aggregation: he supposed that there was an objectively 'correct', but unknown preference order over the alternatives, and voters receive noisy signals of this true preference order (cf.
367:: norms imply that behavior (e.g. retirement ages, cropsharing contracts) exhibits a higher degree of conformity and lower responsiveness to economic conditions than predicted by standard economic models.
326:: the act of learning changes the thing to be learned. There is a complex feedback between a player's beliefs, their actions and the actions of others, which makes the data-generating process exceedingly
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focuses on whether the actions of a small group of players end up conforming to some notion of equilibrium. This is a challenging problem, because social systems are
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and its application to the study of institutional and technological change, as well as the theory of learning in games. He is currently centennial professor at the
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2014), Young has showed how the topology of a social network affects the rate and nature of diffusion under particular adoption rules at the individual level.
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and
Wentzell's (1984) theory of large deviations for continuous time-processes, Dean Foster and Peyton Young (1990) developed the more powerful concept of
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Nagarajan, Mahesh; Sošić, Greys (2008). "Game-theoretic analysis of cooperation among supply chain agents: Review and extensions".
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himself was aware of the Kemeny-Young rule and its maximum-likelihood interpretation, but was unable to clearly express his ideas.
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measure of a player's productivity in a cooperative game and makes it particularly appealing for cost allocation models.
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405:: Individuals are likely to adopt an innovation when a critical mass of individuals in their group has adopted it.
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487:). Using a simple probabilistic model for these noisy signals, Young showed that the Kemeny–Young method was the
412:: Individuals observe the payoffs of adopters and adopt the innovation when these payoffs are sufficiently high.
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398:: Individuals adopt an innovation (a new idea, product or practice) following contact with existing adopters.
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353:: once norms are in place, they persist for long periods of time despite changing external conditions.
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Geoffroy De
Clippel Roberto Serrano (2008). "Marginal Contributions and Externalities in the Value".
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Whereas evolutionary game theory studies the behavior of large populations of agents, the theory of
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Innovation
Diffusion in Heterogeneous Populations: Contagion, Social Influence and Social Learning
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from 1994, until moving to Oxford as James Meade
Professor of Economics in 2007. In 2004 he was a
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191:(born March 9, 1945) is an American game theorist and economist known for his contributions to
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because if there is a Condorcet winner, it will always be ranked as the most popular choice.
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Casajus, André; Huettner, Frank (2014). "Weakly monotonic solutions for cooperative games".
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from 1992 to 1994. Young was Scott & Barbara Black Professor of Economics at the
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Competition and Custom in Economic Contracts: A Case Study of Illinois Agriculture
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Individual Strategy and Social Structure: An Evolutionary Theory of Institutions
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Stochastic Learning Dynamics and Speed of Convergence in Population Games
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counts to identify the most popular choices in an election. It is a
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H. P. Young, "Group choice and individual judgements", Chapter 9 of
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On the Impossibility of Predicting the Behavior of Rational Agents
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edited by B. Grofman and G. Owen (1986), JAI Press, 113–122.
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Proceedings of the National Academy of Sciences of the USA
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Conventional concepts of dynamic stability, including the
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His first academic post was at the graduate school of the
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Learning Efficient Nash Equilibria in Distributed Systems
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of the true preference order. Young further argues that
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A Consistent Extension of Condorcet's Election Principle
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In 1966, he graduated cum laude in general studies from
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Fast Convergence in Evolutionary Equilibrium Selection
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Young (1985) has contributed an axiomatization of the
199:, James Meade Professor of Economics Emeritus at the
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Optimal ranking and choice from pairwise comparisons
667:Learning, Hypothesis Testing, and Nash Equilibrium
851:). Washington, D. C.: The Brookings Institution.
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787:Proceedings of the National Academy of Sciences
742:Proceedings of the National Academy of Sciences
682:The Diffusion of Innovations in Social Networks
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255:Policy in the School of Public Affairs at the
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783:Rapid Innovation Diffusion in Social Networks
723:Gaming Performance Fees by Portfolio Managers
535:Information pooling and group decision making
871:. Princeton NJ: Princeton University Press.
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239:. He completed a PhD in Mathematics at the
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1016:with his CV and full list of publications.
504:J. Kemeny, "Mathematics without numbers",
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630:Perspectives on public choice: a handbook
473:The Kemeny–Young method was developed by
1014:Young's page at the University of Oxford
977:European Journal of Operational Research
686:The Economy as a Complex Evolving System
542:Monotonic solutions of cooperative games
304:Individual Strategy and Social Structure
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214:Peyton Young was named a fellow of the
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837:. Oxford UK: Oxford University Press.
105:American Political Science Association
94:Applications of Game Theory to Finance
1202:North Shore Country Day School alumni
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571:Stochastic Evolutionary Game Dynamics
224:American Academy of Arts and Sciences
546:International Journal of Game Theory
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257:University of Maryland, College Park
601:An Evolutionary Model of Bargaining
521:SIAM Journal on Applied Mathematics
110:Mathematical Association of America
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1187:Fellows of the Econometric Society
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835:Strategic Learning and Its Limits
751:B.S.R. Pradelski and H.P Young, "
738:The Dynamics of Social Innovation
561:American Political Science Review
372:Local conformity/global diversity
335:Strategic Learning and its Limits
1192:Johns Hopkins University faculty
1182:21st-century American economists
620:Journal of Economic Perspectives
515:H. P. Young and A. Levenglick, "
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869:Equity: In Theory and Practice
727:Quarterly Journal of Economics
575:Theoretical Population Biology
287:evolutionarily stable strategy
61:North Shore Country Day School
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1177:University of Michigan alumni
1024:Mathematics Genealogy Project
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798:The Evolution of Social Norms
781:G. Kreindler and H.P Young, "
766:G. Kreindler and H.P Young, "
647:, no. 22 (2001), 12848–12853.
222:in 2007, and a fellow of the
1217:Brookings Institution people
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586:The Evolution of Conventions
557:Condorcet's Theory of Voting
489:maximum likelihood estimator
382:The Diffusion of Innovations
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772:Games and Economic Behavior
757:Games and Economic Behavior
712:Games and Economic Behavior
708:Learning by Trial and Error
671:Games and Economic Behavior
650:H.P Young and M.A. Burke, "
267:Distinguished Chair at the
252:City University of New York
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989:10.1016/j.ejor.2006.05.045
950:Journal of Economic Theory
873:Contents and introduction.
863:Contents and introduction.
853:Contents and introduction.
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811:I. Arieli and H.P Young, "
802:Annual Review of Economics
721:D. Foster and H.P Young, "
665:D. Foster and H.P Young, "
635:D. Foster and H.P Young, "
605:Journal of Economic Theory
569:D. Foster and H.P Young, "
566:, no. 2 (1988), 1231–1244.
197:London School of Economics
145:London School of Economics
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245:combinatorial mathematics
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656:American Economic Review
526:, no. 2 (1978), 285–300.
485:Condorcet's jury theorem
302:In an influential book,
280:Evolutionary game theory
261:Johns Hopkins University
193:evolutionary game theory
79:Evolutionary Game Theory
1167:American game theorists
898:August 8, 2007, at the
444:The Kemeny-Young Method
173:Thomas Frederick Storer
1172:Harvard College alumni
625:, no.1 (1995), 51–64.
552:, No. 2 (1985), 65–72.
241:University of Michigan
227:distributive justice.
108:Lester R. Ford Award,
103:George Hallett Award,
69:University of Michigan
894:Game Theory Society
847:, 2nd edition (with
793:(2014), 10881–10888.
616:Optimal Voting Rules
493:Marquis de Condorcet
460:preferential ballots
297:stochastic stability
231:Education and career
201:University of Oxford
149:University of Oxford
91:Distributive justice
1061:Game Theory Society
845:Fair Representation
464:pairwise comparison
451:Kemeny–Young method
269:University of Siena
216:Econometric Society
189:Hobart Peyton Young
1059:Presidents of the
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703:(2009), 1899–1924.
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468:Condorcet method
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403:Social Influence
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341:Social Norms
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188:
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177:Jack Edmonds
141:Institutions
116:
88:Social Norms
18:
1162:1945 births
1136:(2018–2020)
1130:(2016–2018)
1124:(2014–2016)
1118:(2012–2014)
1112:(2010–2012)
1110:Eric Maskin
1095:(2008–2010)
1093:Sergiu Hart
1089:(2006–2008)
1083:(2003–2006)
1077:(1999–2003)
956:: 162–172.
791:111 Suppl 3
475:John Kemeny
365:Compression
351:Persistence
131:Game Theory
49:Nationality
1156:Categories
1081:Ehud Kalai
879:References
458:that uses
37:1945-03-09
1068:1999–2010
997:0377-2217
921:CiteSeerX
480:epistemic
396:Contagion
265:Fulbright
127:Economics
896:Archived
506:Daedalus
293:Freidlin
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892:Members
358:Tipping
135:Finance
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