Tobias Galla, Manchester
Game theory describes the interaction of agents in competitive strategic situations. Traditional approaches focus on the identification of static equilibria, representing the outcomes for fully rational players. Alternatively one can consider the dynamics of evolving populations of agents, and their learning from past experience. In this talk I will briefly introdcue the basic concepts of evolutionary game theory, and then focus on the effects intrinsic noise, induced by imperfect sampling of the opponents' moves, has on adaptive learning in simple games. I will also show how chaotic motion can arise in games of with a large number of strategies.
Reference: T. Galla, Intrinsic noise in game dynamical learning, Phys. Rev. Lett. 103, 198702 (2009)