Abstract: Robert Axelrod conducted two computer
tournaments to find an effective strategy for the Iterated Prisoner's Dilemma
(IPD). Surprisingly, the simplest strategy submitted was the winner in both
tournaments. The winning strategy was Tit-For-Tat, the strategy that
cooperates on the first move and thereafter does whatever the other player
did in the previous move. The selected chapters explain why understanding
the IPD is important, how tournament results reveal what it takes to be
successful in this context, and why reciprocity works well when paired with a
wide range of strategies. Other chapters describe applications (including
the "live and let live" system in trench warfare in World War I), provide
theorems about the evolution of cooperation, and offer advice on how to
David F. Batten, Discovering Artificial Economics, Westview Press, 2000, Chapters 1-5.
NOTE: The Batten book is unfortunately out of print. However, a pdf file for the entire Batten book (including figures) can be accessed
Samuel Bowles, "Prologue"(pdf,89KB),
Microeconomics: Behavior, Institutions, and Evolution, Princeton
University Press, Princeton, N.J., 2003.
Colin F. Camerer, George Loewenstein, and Matthew Rabin, Advances in Behavioral Economics, Princeton University Press, Princeton, NJ, 776pp., 2003. The introductory chapter by Camerer and Loewenstein titled
Behavioral Economics: Past, Present, Future is particularly recommended.
Abstract: From the publisher: "Behavioral economics uses facts, models, and methods from neighboring sciences such as psychology, sociology, anthropology, and biology to establish descriptively accurate findings about human cognitive ability and social interaction and to explore the implications of these findings for economic behavior. ... Twenty years ago, behavioral economics did not exist as a field. Most economists were deeply skeptical--even antagonistic--toward the idea of importing insights from psychology into their field. Today, behavioral economics has become virtually mainstream. It is well represented in prominent journals and top economics departments, and behavioral economists, including several contributors to this volume, have garnered some of the most prestigious awards in the profession. This book assembles the most important papers on behavioral economics published since around 1990. Among the 25 articles are many that update and extend earlier foundational contributions, as well as cutting-edge papers that break new theoretical and empirical ground."
Colin F. Camerer is Rea A. and Lela G. Axline Professor of Business Economics at the California Institute of Technology. He is the author of "Behavioral Game Theory "(Princeton). George Loewenstein is Professor of Economics and Psychology at Carnegie Mellon University. Matthew Rabin, Professor of Economics at the University of California, Berkeley, received the John Bates Clark Medal of the American Economics Association for 2001.
Martin Neumann, "Homo Socionicus: A Case Study of Simulation Models of Norms"(html),
Journal of Artificial Societies and Social Simulation, 11(4)6 .
Abstract: "This paper describes a survey of normative agent-based social simulation models. These models are examined from the perspective of the foundations of social theory. Agent-based modelling contributes to the research program of methodological individualism. Norms are a central concept in the role-theoretic concept of action in the tradition of Durkheim and Parsons. This paper investigates to what extent normative agent-based models are able to capture the role-theoretic concept of norms. Three methodological core problems are identified: the question of norm transmission, normative transformation of agents and what kind of analysis the models contribute. It can be shown that initially the models appeared only to address some of these problems rather than all of them simultaneously. More recent developments, however, show progress in that direction. However, the degree of resolution of intra agent processes remains too low for a comprehensive understanding of normative behaviour regulation."
Leigh Tesfatsion, "Modeling Behavior, Learning, and Social Interactions in Dynamic Market Contexts: An Agent-Based Computational Approach to Behavioral Economics"(pdf,306KB).
Abstract: This presentation addresses how core behavioral economics concerns (human cognition and social interactions) might be constructively modeled for dynamic markets using powerful new computer capabilities.
Abstract: In the late 1970s and early 1980s, Robert Axelrod conducted several
Iterated Prisoner's Dilemma (IPD) computer tournaments to explore the
conditions under which cooperation based on reciprocity could evolve and
persist even among self-interested individuals. For example, in his first
tournament, game theorists from all over the world were solicited for IPD
strategies in the form of computer algorithms, and the submitted strategies
were then pitted against each other in repeated round-robin plays of the IPD.
The surprising winner was Tit-For-Tat, a simple strategy submitted by Anatol
Rapoport (University of Michigan): Start by cooperating, and thereafter do
whatever your partner did in the previous game play. This book summarizes
his tournament findings and uses these findings to generate thought-provoking
implications for private behavior and public policy in various concrete
Robert Axelrod, "The Importance of Being Nice, Retaliatory, Forgiving,
and Clear", The Economist, November 9, 1985.
Robert Axelrod, "An Evolutionary Approach to Norms", American
Political Science Review, Vol. 80, 1986, pp. 1095-1111. Published
article available at
Abstract: This article develops an agent-based model with a simple form of
learning using the genetic algorithm to explore what can happen when many
agents adapt to each other's behavior over time. Agents can be more or less
bold (say by cheating), and more or less vengeful (say by reporting
cheaters). The model shows the conditions under which a collective action
problem can be solved by a self-sustaining metanorm: punish those who do not
enforce the norm because others might punish you for not doing so.
Robert Axelrod, The Complexity of Cooperation: Agent-Based Models of
Conflict and Cooperation, Princeton University Press, 1997.
Jonathan Bendor and Piotr Swistak, "The Evolutionary Advantage of
Conditional Cooperation", Complexity, Vol. 4/No. 2, November/December
Jeffrey Carpenter, "Evolutionary Models of Bargaining: Comparing
Agent-Based Computational and Analytical Approaches to Understanding
Convention Evolution", Computational Economics 19(1), 2002, pp.
25-49. Downloadable at
"Just How (Un)realistic are Evolutionary Algorithms as
Representations of Social Processes?"(html),
Journal of Artificial Societies and
Social Simulation 1:3 (1998). [electronic journal]
"Intelligent Social Learning"(html),
Journal of Artificial Societies and Social Simulation 4:1, 2001.
Joshua M. Epstein, "Zones of Cooperation in Demographic Prisoner's
Dilemma", Complexity, Vol. 4/No. 2, November/December 1998, 36-48.
Joshua M. Epstein, "Learning to be Thoughtless: Social Norms and
Individual Competition", Computational Economics Vol. 18, 2001, 9-24.
Abstract: Epstein uses an agent-based model to study experimentally an
important observed aspect of social norm evolution: namely, that the amount
of time an individual devotes to thinking about a behavior tends to be
inversely related to the strength of the social norms that relate to this
behavior. In the limit, once a behavioral norm is firmly entrenched in a
society, individuals tend to conform to the norm without explicit thought.
Epstein's innovative model permits agents to learn how to behave (what
behavioral norm to adopt) but it also permits agents to learn how much to
think about how to behave.
Joshua M. Epstein and Robert Axtell, Growing Artificial Societies:
Social Science from the Bottom Up, MIT Press, 1996. (Sugarscape)
Herb Gintis, Game Theory Evolving(html),
Princeton University Press, June 2000.
Abstract: This book is strongly problem-oriented. It stresses agent-based
evolutionary dynamics, using illustrations from both economics and biology.
The author highlights the `low rationality' aspects of game dynamics. He
particularly emphasizes the need for better models of the individual actor in
view of the large number of anomalies in the predictions of the traditional
model of the `rational actor' uncovered in laboratory experiments with human
Jonathan Haas, "A Brief Consideration of Cultural Evolution: Stages,
Agents, and Tinkering", Complexity, Vol. 3/No. 3, January/February
Understanding and explaining complexity across time and cultures.
Douglas R. Hofstadter, "Computer Tournaments of the Prisoner's Dilemma
Suggest How Cooperation Evolves"(pdf,856KB),
Scientific American, May 1983.
Abstract: Hofstadter explains Robert Axelrod's computer tournaments, which
explored the evolution of cooperation in the Iterated Prisoner's Dilemma.
For the original work, see above.
David M. Kreps, Game Theory and Economic Modelling,
Clarendon Press, Oxford, 1991.
Abstract: This book presents basic game theory tools, illustrated graphically and by numerous
examples, and discusses the questions that these tools can and cannot answer.
Martin A. Nowak, Karen M. Page, and Karl Sigmund, "Fairness
Versus Reason in the Ultimatum Game", Science, Vol. 289, September
8, 2000, pp. 1773-1775.
Published article freely available at
The Science Magazine.
Abstract: The authors consider the Ultimatum Gamein which two players are
offered a chance to win a certain sum of money. One player, the proposer,
gets to offer a portion of the sum to the other player, retaining the rest.
The second player gets to accept or reject the offer, with rejection
resulting in no money for either player. The rational solution, according to
game theory, is for the proposer to offer as little as possible and for the
other player to accept. When humans play the game, however, the most
frequent offer is an equal ("fair") share. The authors employ evolutionary
dynamics to explain how this "irrational" anchoring on fair shares might have
evolved among humans in part through a rational concern for reputation.
Specifically, accepting low offers, if generally known and remembered,
increases the chances of receiving low offers in subsequent encounters; and
making low offers becomes irrational if low offers are not accepted.
Brian Skyrms, Evolution of the Social Contract, Cambridge
University Press, 1996.
Abstract: From the book cover: "In this pithy and highly readable book, Brian
Skyrms, a recognized authority on game theory and decision theory,
investigates traditional problems of the social contract in terms of
evolutionary dynamics. Game theory is skillfully employed to offer quite new
interpretations of a wide variety of social phenomena, including justice,
mutual aid, commitment, convention, and meaning."
H. Peyton Young,
"Social Dynamics: Theory and Applications",
in Leigh Tesfatsion and Kenneth L. Judd (editors),
Handbook of Computational Economics, Vol. 2: Agent-Based Computational
Economics, Handbooks in Economics Series, North-Holland/Elsevier, Amsterdam,
Agent-based models typically involve large numbers of
interacting individuals with widely differing characteristics, rules
of behavior, and sources of information. The dynamics of such
systems can be extremely complex due to their high dimensionality.
This chapter discusses a general method for rigorously analyzing the
long-run behavior of such systems using the theory of large
deviations in Markov chains. The theory highlights certain
qualitative features that distinguish agent-based models from more
conventional types of equilibrium analysis. Among these
distinguishing features are: local conformity versus global
diversity, punctuated equilibrium, and the persistence of particular
states in the presence of random shocks. These ideas are illustrated
through a variety of examples, including competition between
technologies, models of sorting and segregation, and the evolution
of contractual customs.
Chris Cook (Computer Science Department, Iowa State University,
Ames) has developed the Axelrod Tournament, a computational laboratory
that captures and extends the salient aspects of Axelrod's 1979 tournament.
The Axelrod Tournament permits a user to specify as treatment factors the
number of tournament iterations, the total number of agents (strategies)
comprising the initial tournament population, the types of agents in this
population, and the form of payoff matrix for each agent type. The latter
feature extends Axelrod's original tournament by permitting matched agents to
engage in a wide variety of two-player games (Chicken, Stag Hunt, etc.)
depending on their specified types. The user can then observe the
comparative performance over time of each agent, and each agent type, by
means of run-time graphical and text displays. The Axelrod Tournament is
available as freeware under the GNU Public License. Automatic installation
software for this computational laboratory, together with more detailed
information about its capabilities and implementation, can be obtained at
The Axelrod Tournament: Demonstration Software (html).
Leigh Tesfatsion (Iowa State University) and coauthors have developed the
Trade Network Game (TNG) Laboratory
for exploring the evolution of trade networks among strategically interacting
traders. The TNG traders repeatedly choose and refuse their trade partners
on the basis of expected payoffs, and trades are modeled as two-person games
in which the traders can either "cooperate" or "defect". The TNG user can
set trade payoffs to mimic a wide variety of game configurations (e.g.,
prisoner's dilemma, chicken, stag hunt,...). The TNG lab permits systematic
experimentation to determine conditions under which the trade networks that
evolve over time support cooperative behaviors among buyers and sellers
(e.g., workers and employers).
Resource Sites, Groups, and Some Early Individual Researchers
W. Brian Arthur,
(Santa Fe Institute,
New Mexico): Designing economic agents that act like human agents; The El
Farol Bar Problem; Artificial stock market modelling; Effects of positive
(Political Science and Public Policy, School of Public Policy Studies,
University of Michigan, Ann Arbor): Complexity of cooperation; Evolution of
(Krasnow Institute for Advanced Study, George Mason University, Arlington, VA): Sugarscape model; Growing
artificial societies from the bottom up; Size distribution of firms;
Environmental economics and regulation; Global change science and policy.
(Santa Fe Institute, University of Sienna, and Emeritus Professor of
Economics at the University of Massachusetts, Amherst, MA): Co-evolution of
preferences, institutions, and behavior; Causes and consequences of economic
(Department of Anthropology, UCLA): Evolutionary psychology of mechanisms
that give rise to, and shape, human culture; Population dynamic processes and
human cultural variation.
(Laboratory of Agent-Based Social Simulation, Institute for Cognitive Science and Technology, CNR - Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy): Simulation of social behavior;
External social sources of constraints to cognitive agents' autonomy; Formal
models for representing and treating the mental attitudes involved in social
action, social groups, and collective agents; Emergence of norms.
Joshua M. Epstein
(Brookings Institution, Washington, D.C.): Sugarscape; Growing
societies from the bottom up; Modelling of complex social systems,
with application to international security, environmental, and policy areas.
(External Faculty Member of the Santa Fe Institute, and Emeritus Professor of
Economics at the University of Massachusetts, Amherst) is interested in
agent-based evolutionary game dynamics, the evolution of reciprocity, the
moral economy of communities, and the evolution of social norms. He has
developed Borland Pascal 7.0 code that implements a general iterated game of
the following form. Agents in a population are randomly paired for game play
and obtain fitness payoffs. A genetic algorithm involving haploid
reproduction and mutation is then used to evolve the agent population.
(Department of Psychology, University of British Columbia, CA): Biological evolution
of cultural transmission and learning capacities; Evolution of cooperation;
Common pool resource and public goods problems; Cross-cultural experimental
games; Economic behavior and ethnography among the Mapuche of southern Chile.
John M. Orbell
(Emeritus, Political Science Department, University of Oregon, Eugene):
Agent-based computational modelling of socioeconomic systems; Evolution of
cooperation and trust; Coordination issues and social chess; Intersection of
evolutionary theory, cognitive science, and the study of human social
relations; Evolutionary psychology. Orbell has designed various
real-agent experiments and written code to implement experiments with
(School of Social Sciences, UC Irvine, CA): Evolution of
conventions and social contracts; Inductive logic; Decision theory; Rational deliberation; Metaphysics of logical atomism, causality, and Truth.
(Economics, Iowa State University) and co-authors have investigated the
evolution of cooperation in iterated prisoner's dilemma games in which the
players are able to choose and refuse their partners on the basis of
continually updated partner preferences. This work was later extended by
Tesfatsion to a more general
"Trade Network Game (TNG)"
of buyers, sellers, and dealers who repeatedly seek preferred trade partners
and whose trade interactions are modelled as two-person games. Source code
for the TNG is available online as freeware (see above).
(Department of Economics, Queen Mary and Westfield College, University of
London): Dynamics of interactive market processes; Emergent properties of
evolving market structures and outcomes.
H. Peyton Young
(Department of Economics, Johns Hopkins University, Baltimore, Maryland):
Individual strategy and social structure; Learning and evolution in games;
Bargaining and negotiation; Public finance; Political representation and
voting; Distributive justice.