Emergence of Cooperation in a Pursuit-Evasion Game

Geoff Nitschke

Abstract: This research concerns the comparison of three different artificial evolution approaches to the design of cooperative behavior in a group of simulated mobile robots. The first and second approaches, termed: single pool and plasticity, are characterized by robots that share a single genotype, though the plasticity approach includes a learning mechanism. The third approach, termed: multiple pools, is characterized by robots that use different genotypes. The application domain implements a pursuit-evasion game in which teams of robots of various sizes, termed: predators, collectively work to capture either one or two others, termed: prey. These artificial evolution approaches are also compared with a static rule based cooperative pursuit strategy specified a priori. Results indicate that the multiple pools approach is superior comparative to the other approaches in terms of measures defined for prey-capture strategy performance. That is, this approach facilitated specialization of behavioral roles allowing it to be effective for all predator team sizes tested.