The impact of connection topology and agent size on cooperation in the iterated prisoner's dilemma

Abstract

This study revisits earlier work, concerning the evolutionary trajectory of agents trained to play iterated prisoner's dilemma on a combinatorial graph. The impact of different connection topologies, used to mediate both the play of prisoner's dilemma and the flow of genes during selection and replacement, is examined. The variety of connection topologies, stored as combinatorial graphs, is revisited and the analysis tools used are substantially improved. A novel tool called the play profile summarizes the distribution of behaviors over multiple replicates of the basic evolutionary algorithm and through multiple evolutionary epochs. The impact of changing the number of states used to encode agents is also examined. Changing the combinatorial graph on which the population resides is found to yield statistically significant differences in the play profiles. Changing the number of states in agents is also found to produce statistically significant differences in behavior. The use of multiple epochs in analysis of agent behavior demonstrates that the distribution of behaviors changes substantially over the course of evolution. The most common pattern is for agents to move toward the cooperative state over time, but this pattern is not universal. Another clear trend is that agents implemented with more states are less cooperative.