This paper investigates the properties of the most common form of reinforcement learning (the "basic model" of Erev and Roth, American Economic Review, 88, 848-881, 1998). Stochastic approximation theory has been used to analyse the local stability of fixed points under this learning process....

In this paper we study a stochastic learning model for 2, 2 normal form games that are played repeatedly. The main emphasis is put on the emergence of cycles. We assume that the players have neither information about the payoff matrix of their opponent nor about their own. At every round each...

Win Stay, Lose Shift as well as imitation strategies for iterated games rely on an aspiration level. With both learning rules a move is repeated unless the pay-off fell short of the aspiration level. I investigate social adaptation mechanisms for the aspiration level and their impact on the...

One-sided confidence intervals and overall p-values for group-sequential designs are typically based on a sample space ordering which determines both the overall p-value and the corresponding confidence bound. Accordingly, the strength of evidence against the null hypothesis is consistently...

In this paper we study a simple learning paradigm for iterated normal form games in an evolutionary context. Following the decision theoretic concept of satisficing we design players with a certain aspiration level. If their payoff is below this level, they change their current action, otherwise...