Co-evolution of cooperation in a pursuit evasion game

This research concerns the comparison of different artificial evolution approaches to the design of cooperative behavior in a team of simulated mobile robots co-evolved against a second team. 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 is a pursuit-evasion game in which a team of three robots termed: pursuers, collectively work to immobilize one of the three robots of the other team, termed: evaders. Results indicate that the multiple pools approach applied within a competitive co-evolution process yields superior performance comparative to the other approaches. Specifically, the co-evolutionary process allows the multiple pools approach to ´bootstrap´ complementary behavioral roles, facilitating the evolution of a stable cooperative pursuit strategy.