Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-25T18:31:52.704Z Has data issue: false hasContentIssue false
Series:   Elements in Decision Theory and Philosophy

Evolutionary Game Theory

Published online by Cambridge University Press:  07 March 2023

J. McKenzie Alexander
J. McKenzie Alexander
Affiliation:
London School of Economics and Political Science

Summary

Evolutionary game theory originated in population biology from the realisation that frequency-dependent fitness introduced a strategic element into evolution. Since its development, evolutionary game theory has been adopted by many social scientists, and philosophers, to analyse interdependent decision problems played by boundedly rational individuals. Its study has led to theoretical innovations of great interest for the biological and social sciences. For example, theorists have developed a number of dynamical models which can be used to study how populations of interacting individuals change their behaviours over time. In this introduction, this Element covers the two main approaches to evolutionary game theory: the static analysis of evolutionary stability concepts, and the study of dynamical models, their convergence behaviour and rest points. This Element also explores the many fascinating, and complex, connections between the two approaches.
Get access

Keywords

evolutionary game theorybounded rationalityevolutionary dynamicscooperationlocal interactions
Type
Element
Information
Series: Elements in Decision Theory and Philosophy
Online ISBN: 9781108582063
Publisher: Cambridge University Press
Print publication: 23 March 2023

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alexander, J. McKenzie (2007). The Structural Evolution of Morality. Cambridge University Press.Google Scholar
Alexander, J. McKenzie (2009). ‘Social Deliberation: Nash, Bayes, and the Partial Vindication of Gabriele Tarde’. Episteme 6: 164–84.Google Scholar
Alexander, J. McKenzie (2016). ‘Evolutionary Game Theory’. In Batchelder, William H., Colonius, Hans, Dzhafarov, Ehtibar N. and Myung, Jay, eds., New Handbook of Mathematical Psychology, Cambridge University Press, volume 1, chapter 6, pp. 322–73.Google Scholar
Arneodo, Alain, Coulett, Pierre, and Tresser, Charles (1980). ‘Occurence of Strange Attractors in Three-Dimensional Volterra Equations’. Physics Letters 79A: 259–63.Google Scholar
Artinger, Florian M., Gigerenzer, Gerd and Jacobs, Perke (2022). ‘Satisficing: Integrating Two Traditions’. Journal of Economic Literature 60: 598–635.Google Scholar
Balkenborg, Dieter and Schlag, Karl H. (2001). ‘Evolutionarily Stable Sets’. International Journal of Game Theory 29: 571–95.Google Scholar
Barabási, Albert-László and Albert, Réka (1999). ‘Emergence of Scaling in Random Networks’. Science 286: 509–12.Google Scholar
Björnerstedt, Jonas and Weibull, Jörgen (1999). ‘Nash Equilibrium and Evolution by Imitation’. In Arrow, Kenneth J., Colombatto, Enrico and Perlman, Mark, eds., The Rational Foundations of Economic Behavior, St. Martin’s Press.Google Scholar
Bomze, Immanuel M. (1983). ‘Lotka-Volterra Equation and Replicator Dynamics: A Two-Dimensional Classification’. Biological Cybernetics 48: 201–11.Google Scholar
Brown, George W. and von Neumann, John (1950). ‘Solutions of Games by Differential Equations’. In Contributions to the Theory of Games, Princeton University Press, number 24 in Annals of Mathematical Studies.Google Scholar
Chao, Lin and Levin, Bruce R. (1981). ‘Structured Habitats and the Evolution of Anticompetitor Toxins in Bacteria’. Proceedings of the National Academy of Sciences 78: 6324–8.Google Scholar
Devaney, Robert L. (1989). An Introduction to Chaotic Dynamical Systems. Addison-Wesley Publishing Company, second edition.Google Scholar
Dunbar, Robin I. M. (1993). ‘Coevolution of Neocortical Size, Group Size and Language in Humans’. Behavioral and Brain Sciences 16: 681–94.Google Scholar
Dunbar, Robin I. M. (1992). ‘Neocortex Size as a Constraint on Group Size in Primates’. Journal of Human Evolution 22: 469–93.Google Scholar
Flood, Merrill M. (1952). ‘Some Experimental Games’. Technical report, The RAND Corporation. RM-789-1.Google Scholar
Franchetti, Francisco and Sandholm, William H. (2013). ‘An Introduction to Dynamo: Diagrams for Evolutionary Game Dynamics’. Biological Theory 8: 167–78.Google Scholar
Gigerenzer, Gerd, Todd, Peter M. and the ABC Research Group (1999). Simple Heuristics That Make Us Smart. Oxford University Press.Google Scholar
Gintis, Herbert (2009). Game Theory Evolving. Princeton University Press, second edition.Google Scholar
Gould, Stephen Jay (1980). The Panda’s Thumb: More Reflections in Natural History. W. W. Norton & Company.Google Scholar
Harsanyi, John C. (1967a). ‘Games with Incomplete Information Played by Bayesian Players. Part I. The Basic Model’. Management Science 14: 159–82.Google Scholar
Harsanyi, John C. (1967b). ‘Games with Incomplete Information Played by Bayesian Players. Part II. Bayesian Equilibrium Points’. Management Science 14: 320–34.Google Scholar
Harsanyi, John C. (1967c). ‘Games with Incomplete Information Played by Bayesian Players. Part III. The Basic Probability Distribution of the Game’. Management Science 14: 486–502.Google Scholar
Hilborn, Robert C. (2000). Chaos and Nonlinear Dynamics: An Introduction for Scientists and Engineers. Oxford University Press, second edition.Google Scholar
Hofbauer, Josef and Sigmund, Karl (2002). Evolutionary Games and Population Dynamics. Cambridge University Press.Google Scholar
Hofbauer, Josef and Sandholm, William H. (2011). ‘Survival of Dominated Strategies under Evolutionary Dynamics’. Theoretical Economics 6: 341–77.Google Scholar
Hofbauer, Josef, Schuster, Peter and Sigmund, Karl (1979). ‘A Note on Evolutionary Stable Strategies and Game Dynamics’. Journal of Theoretical Biology 81: 609–12.Google Scholar
Huberman, Bernardo A. and Natalie, S. Glance, (1993). ‘Evolutionary Games and Computer Simulations’. Proceedings of the National Academy of Sciences 90: 7716–18.Google Scholar
Lindenfors, Patrik, Wartel, Andreas and Lind, Johan (2021). “‘Dunbar’s Number” Deconstructed’. Biology Letters 17: 202110158.Google Scholar
Luce, R. Duncan and Raiffa, Howard (1957). Games and Decisions: Introduction and Critical Survey. John Wiley and Sons, Inc.Google Scholar
Maynard Smith, John and Price, George (1973). ‘The Logic of Animal Conflict’. Nature 246: 15–18.Google Scholar
McKelvey, Richard D. and Thomas, R. Palfrey, (1992). ‘An Experimental Study of the Centipede Game’. Econometrica 60: 803–36.CrossRefGoogle Scholar
Milgram, Stanley (1963). ‘Behavioral Study of Obedience’. Journal of Abnormal and Social Psychology 67: 371–8.Google Scholar
Milgram, Stanley (1967). ‘The Small World Problem’. Psychology Today 2: 61–7.Google Scholar
Mohseni, Aydin (2015). The Limits of Equilibrium Concepts in Evolutionary Game Theory. Master’s thesis, Carnegie Mellon University.Google Scholar
Moran, Patrick A. P. (1958). ‘Random Processes in Genetics’. In Mathematical Proceedings of the Cambridge Philosophical Society. Cambridge University Press, volume 54, pp. 60–71.Google Scholar
Nash, John (1950a). Non-cooperative Games. PhD thesis, Princeton University.Google Scholar
Nash, John F. (1950b). ‘Equilibrium Points in n-Person Games’. Proceedings of the National Academy of Sciences 36: 48–9.Google Scholar
Nowak, Martin A. (1990). ‘An Evolutionary Stable Strategy May Be Inaccessible’. Journal of Theoretical Biology 142: 237–41.Google Scholar
Nowak, Martin A. (2006). Evolutionary Dynamics: Exploring the Equations of Life. Harvard University Press.Google Scholar
O’Connor, Cailin (2019). The Origins of Unfairness: Social Categories and Cultural Evolution. Oxford University Press.Google Scholar
Oechssler, Jörg (1997). ‘An Evolutionary Interpretation of Mixed-Strategy Equilibria’. Games and Economic Behavior 21: 203–37.Google Scholar
Pacuit, Eric and Roy, Olivier (2017). ‘Epistemic Foundations of Game Theory’. In Zalta, E. N., ed., The Stanford Encyclopedia of Philosophy, Metaphysics Research Lab, Stanford University. Summer 2017 edition.Google Scholar
Rosenthal, Robert W. (1981). ‘Games of Perfect Information, Predatory Pricing, and the Chain Store’. Journal of Economic Theory 25: 92–100.Google Scholar
Rubinstein, Ariel (1991). ‘Comments on the Interpretation of Game Theory’. Econometrica 59: 909–24.Google Scholar
Rubinstein, Ariel (1998). Modeling Bounded Rationality. Massachusetts Institute of Technology Press.Google Scholar
Samuelson, Larry (1996). ‘Bounded Rationality and Game Theory’. The Quarterly Review of Economics and Finance 36, Supplement 1: 17–35.Google Scholar
Sandholm, William H. (2010). Population Games and Evolutionary Dynamics. Massachusetts Institute of Technology Press.Google Scholar
Sandholm, William H. (2015). ‘Population Games and Deterministic Evolutionary Dynamics’. In Young, H. P. and Zamir, Shmuel, eds., Handbook of Game Theory, Elsevier, volume 4, chapter 13, pp. 720–78.Google Scholar
Simon, Herbert A. (1955). ‘A Behavioral Model of Rational Choice’. The Quarterly Journal of Economics 69: 99–118.CrossRefGoogle Scholar
Simon, Herbert A. (1956). ‘Rational Choice and the Structure of the Environment’. Psychological Review 63: 129.CrossRefGoogle ScholarPubMed
Skyrms, Brian (1990). The Dynamics of Rational Deliberation. Harvard University Press.Google Scholar
Skyrms, Brian (1992). ‘Chaos in Game Dynamics’. Journal of Logic, Language, and Information 1: 111–30.Google Scholar
Skyrms, Brian (1993). ‘Chaos and the Explanatory Significance of Equilibrium: Strange Attractors in Evolutionary Game Dynamics’. In Proceedings of the 1992 PSA, volume 2, pp. 374–94.Google Scholar
Skyrms, Brian (2003). The Stag Hunt and the Evolution of Social Structure. Cambridge University Press.Google Scholar
Skyrms, Brian (2010). Signals: Evolution, Learning, & Information. Oxford University Press.CrossRefGoogle Scholar
Skyrms, Brian and Pemantle, Robin (2000). ‘A Dynamic Model of Social Network Formation’. Proceedings of the National Academy of Science 97: 9340–6.Google Scholar
Smead, Rory (2008). ‘The Evolution of Cooperation in the Centipede Game with Finite Populations’. Philosophy of Science 75: 157–77.Google Scholar
Smith, Michael J. (1984). ‘The Stability of a Dynamic Model of Traffic Assignment: An Application of a Method of Lyapunov’. Transportation Science 18: 245–52.Google Scholar
Spiekermann, Kai P. (2009). ‘Sort Out Your Neighbourhood: Public Good Games on Dynamic Networks’. Synthese 168: 273–94.Google Scholar
Taylor, Peter D. and Leo, B. Jonker, (1978). ‘Evolutionary Stable Strategies and Game Dynamics’. Mathematical Biosciences 40: 145–56.Google Scholar
Thomas, Bernhard (1985). ‘On Evolutionarily Stable Sets’. Journal of Mathematical Biology 22: 105–15.Google Scholar
Vanderschraaf, Peter (2006). ‘War or Peace? A Dynamical Analysis of Anarchy’. Economics & Philosophy 22: 243–79.Google Scholar
Vanderschraaf, Peter (2007). ‘Covenants and Reputations’. Synthese 157:167–95.CrossRefGoogle Scholar
Vickers, Glenn T. and Cannings, Chris (1987). ‘On the Definition of an Evolutionarily Stable Strategy’. Journal of Theoretical Biology 129: 349–53.Google Scholar
John, von Neumann (1928). ‘Zur Theorie der Gesellschaftsspiele’. Mathematische Annalen 100: 295–320. Translated by S. Bargmann as ‘On the Theory of Games of Strategy’, in Contributions to the Theory of Games, volume 4, Annals of Mathematics Studies, 40, pp. 13–43, 1959.Google Scholar
Watts, Duncan J. (1999). Small Worlds: The Dynamics of Networks between Order and Randomness. Princeton University Press.Google Scholar
Watts, Duncan J. and Strogatz, Steven H. (1998). ‘Collective Dynamics of ‘Smallworld’ Networks’. Nature 393: 440–2.Google Scholar
Weibull, Jörgen W. (1995). Evolutionary Game Theory. Massachusetts Institute of Technology Press.Google Scholar
Zeeman, Erik C. (1979). ‘Population Dynamics from Game Theory’. In Global Theory of Dynamical Systems: Proceedings of an International Conference Held at Northwestern University, Evanston, Illinois, June 18–22, 1979. Northwestern: University Press.Google Scholar

Save element to Kindle

To save this element to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Evolutionary Game Theory
Available formats
×

Save element to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Evolutionary Game Theory
Available formats
×

Save element to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Evolutionary Game Theory
Available formats
×