Reinforcement learning and stochastic fictitious play are apparent rivals as models of human learning. They embody quite different assumptions about the processing of information and optimisation. This paper compares their properties and finds that they are far more similar than was thought. In...

Reinforcement learning and stochastic fictitious play are apparent rivals as models of human learning. The embody quite different assumptions about the processing of information and optimisation. This paper compares their properties and finds that they are far more similar than were thought. In...

This paper applies recent advances in the theory of learning to the analysis of consumer behaviour in a dynamic duopoly. Nash equilibrium play is characterised when consumers learn adaptively about the relative quality of the two products. A constrast is made between belief-based and...