Coevolution of Role-Based Cooperation in Multiagent Systems

C.H. Yong, R. Miikkulainen
2009 IEEE Transactions on Autonomous Mental Development  
In tasks such as pursuit and evasion, multiple agents need to coordinate their behavior to achieve a common goal. An interesting question is, how can such behavior be best evolved? A powerful approach is to control the agents with neural networks, coevolve them in separate subpopulations, and test them together in the common task. In this paper, such a method, called Multiagent Enforced SubPopulations (Multiagent ESP), is proposed and demonstrated in a prey-capture task. First, the approach is
more » ... hown to be more efficient than evolving a single central controller for all agents. Second, cooperation is found to be most efficient through stigmergy, i.e., through role-based responses to the environment, rather than communication between the agents. Together these results suggest that role-based cooperation is an effective strategy in certain multiagent tasks.
doi:10.1109/tamd.2009.2037732 fatcat:gesaiklstfbxxo2wwbeptdv5xu