Evolution and Learning in Economic Models

Game theory has been successfully applied in biology as a method for studying evolution. However, biologists approached game theory in a different way as economists have done. In the introduction to his influential book, John Maynard Smith (1982) states the differences between evolutionary game theory —the application of game theory to biology— and the traditional economic approach to game theory. In evolutionary game theory the payoffs of a game are identified with Darwinian fitness, and rationality is replaced with evolutionary stability. The basic object of study is a population of individuals competing with each other for survival and reproduction. This strategic competition is modeled through a game and the strategies correspond to the phenotypes whose survival is in question. The aim is to study the evolution of the different strategies in the population. In an evolutionary game, however, individuals do not consciously choose, but are programmed to play certain strategies. More successful strategies survive with higher probability and reproduce faster. A strategy is said to be evolutionarily stable if, once adopted by all members of the population, a small fraction of so-called mutants —i. e. individuals doing something different— will be selected against. Intuitively, if several strategies are present in a stable situation, they all must be equally successful. In a large population, a stable situation must correspond to a Nash equilibrium. In this way, evolutionary game theory provides foundations for the concept of Nash equilibrium and a different interpretation. Moreover, this interpretation is absent of the rationality assumptions of traditional game theory.