Incorporating Risk Attitude and Reputation into Infinitely Repeated Games and an Analysis on the Iterated Prisoner´s Dilemma

Many real life situations can be modeled as Prisoner´s dilemma. There are various strategies in the literature. However, few of which match the design objectives of an intelligent agent - being reactive and pro-active. In this paper, we incorporate risk attitude and reputation into infinitely repeated games. In this way, we find that the original game matrix can be transformed to a new matrix, which has a kind of cooperative equilibrium. We use the proposed concepts to analyze the Iterated Prisoner´s dilemma. Simulation also shows that agents, which consider risk attitude and reputation in the decision-making process, have improved performance and are reactive as well as pro-active.