Game theoretic equilibria and the evolution of learning
Equilibrium concepts in game theory can be justified as the outcomes of some plausible learning rules. Some scholars have sought a deeper kind of justification arguing that learning rules which do not find equilibria of a game will not be evolutionarily successful. This article presents and examines a model of evolving learning rules. The results are mixed for learning rules that lead to equilibria, showing that they are often successful, but not strongly stable. It is also shown that evolved learning rules, when taken in isolation, may not lead to equilibria. This is a case of reflexive modelling; where game theoretic models are used to assess other features of game theory. I argue that it is possible for reflexive modelling to provide a weak form of justification, but that it falls short in this case.
evolution learning equilibrium game theory evolutionarily stable strategy reflective modelling