Evolutionary game theory

application of game theory to evolving populations in biology

Evolutionary game theory (EGT) is the application of game theory to evolving populations of lifeforms in biology. In this context it defines a framework of contests, strategies, and analytics into which Darwinian competition can be modelled. It originated in 1973 with John Maynard Smith and George R. Price's formalisation of the way in which such contests can be analysed as "strategies" and the mathematical criteria that can be used to predict the resulting prevalence of such competing strategies.

Evolutionary models assume that people choose their strategies through a trial-and-error learning process in which they gradually discover that some strategies work better than others. In games that are repeated many times, low-payoff strategies tend to be weeded out, and an equilibrium may emerge. - Larry Samuelson, 1997.

QuotesEdit

  • Evolutionary game theory originated as an application of the mathematical theory of games to biological contexts, arising from the realization that frequency dependent fitness introduces a strategic aspect to evolution. Recently, however, evolutionary game theory has become of increased interest to economists, sociologists, and anthropologists--and social scientists in general--as well as philosophers.
  • Traditionally, game theory has been seen as a theory of how rational actors behave. Ironically, game theory... has shown... the limited capacity of the concept of rationality alone to predict human behavior. ...Evolutionary game theory deploys the Darwinian notion that good strategies diffuse across populations of players rather than being learned by rational agents. ...[A]gents choose best responses, and otherwise behave as good citizens of game theory society. But they may be pigs, dung beetles, birds, spiders, or even... Trogs and Klingons. How do they accomplish these feats with their small minds and alien mentalities? ...the agent is displaced by the strategy as the dynamic game-theoretic unit. ...[W]e provide agent-based computer simulations of games, showing that really stupid critters can evolve toward the solution of games previously thought to require "rationality" and high-level information processing capacity.
    • Herbert Gintis, Game Theory Evolving: A Problem-Centered Introduction to Modeling Strategic Interaction (2009) 2nd edition, Preface, p. xvi.
  • Ever since Darwin read Malthus, the theory of evolution has benefited from the interaction of ecology with economics. Evolutionary game theory belongs to this tradition: it merges population ecology with game theory.
    • Karl Sigmund and Martin A. Nowak. "Evolutionary game theory." Current Biology 9.14 (1999): R503-R505.
  • Evolutionary game theory is one of the most active and rapidly growing areas of research in economics. Unlike traditional game theory models, which assume that all players are fully rational and have complete knowledge of details of the game, evolutionary models assume that people choose their strategies through a trial-and-error learning process in which they gradually discover that some strategies work better than others. In games that are repeated many times, low-payoff strategies tend to be weeded out, and an equilibrium may emerge.
    • Larry Samuelson. Evolutionary Games and Equilibrium Selection. 1997. Overview.
  • Evolutionary game theory is a way of thinking about evolution at the phenotypic level when the fitnesses of particular phenotypes depend on their frequencies in the population.
  • Current evolutionary game theory — where ideas from evolutionary biology and rationalistic economics meet — emphasizing the links between static and dynamic approaches and noncooperative game theory.
    • Jörgen W. Weibull. Evolutionary game theory. MIT press, 1997. Introduction

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