糖心原创

Abstract: The Individual Evolutionary Learning (IEL) model explains behavior in a wide range of repeated games which have unique Nash equilibria. Using a variation of \better response" strategies, IEL agents are very good at learning to play the Nash equilibrium strategies and their dynamic behavior looks a lot like that of humans in laboratory experiments. In this paper we study whether IEL would also behave in ways similar to humans in games in which there are gains from coordination. To do so we focus on the simplest such game: the 2 person Battle of Sexes game. That game has two pure Nash equilibria, each preferred by one of the players. It is well known that, in laboratory experiments, two patterns of behavior often emerge: the players converge rapidly to one of the Nash equilibria and stay there or the players learn to coordinate their actions and alternate between the Nash equilibria every other round. When IEL considers multi-period strategies, alternating behavior occurs, but only about 1% of the time. This is certainly a lot less often than humans do. Learning alone cannot not explain the human behavior in repeated Battle of Sexes games.