Evolutionary game theory (EGT) is the application of game theory in evolutionary biology. It is used to understand situations in which the benefits of what an organism does depend on what other animals are doing.

EGT studies the dynamics and equilibria of games played by populations of players. The strategies players employ in the games determine their interdependent payoff or fitness. In contrast with the traditional applications of game theory, the players do not act rationally when choosing their strategies, but act instead according to a pre-programmed behavior pattern. A pure strategy is encoded in an individual's genome, which can evolve over time while repeatedly playing a game against other players in a population. The more successful strategies result in more offspring and the game is then iterated and studied.

Recently, evolutionary game theory has increasingly become of interest to economists, sociologists, and anthropologists, as well as philosophers. In these expanded contexts, the ‘evolution’ treated by EGT can refer to systems such as cultural evolution or economic behavior.

The common methodology to study the evolutionary dynamics in games is through replicator equations. Replicator equations assume infinite populations , continuous time, complete mixing and that strategies breed true . The attractors (stable fixed points) of the equations are equivalent with evolutionarily stable strategies.

References

• Maynard Smith, J. (1981) Evolution and the Theory of Games.
• Weibull, J. W. (1995) Evolutionary game theory, MIT Press
• Hofbauer, J. and Sigmund, K. (1998) Evolutionary games and population dynamics, Cambridge University Press

External links

• EGT at the Stanford Encyclopedia of Philosophy
• Google Directory for EGT