ABSTRACT Title of dissertation: AGENT MODELING IN STOCHASTIC REPEATED GAMES

There are many situations in which two or more agents (e.g., human or com-puter decision makers) interact with each other repeatedly in settings that can be modeled as repeated games. In such situations, there is evidence that agents some-times deviate greatly from what conventional game theory would predict. There are several reasons why this might happen, one of which is the focus of this dissertation: sometimes an agent’s preferences may involve not only its own payoff (as specified in the payoff matrix), but also the payoffs of the other agent(s). In such situations, it is important to be able to understand what an agent’s preferences really are, and how those preferences may affect the agent’s behavior. This dissertation studies how the notion of Social Value Orientation (SVO), a construct in social psychology to model and measure a person’s social preference, can be used to improve our understanding of the behavior of computer agents. Most of the work involves the life game, a repeated game in which the stage game is chosen stochastically at each iteration. The work includes the following results: • Using a combination of the SVO theory and evolutionary game theory, w