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Coevolution of Role-Based Cooperation in Multiagent Systems

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2 Author(s)
Yong, C.H. ; Comput. Biol. Lab., Nat. Univ. of Singapore, Singapore, Singapore ; Miikkulainen, R.

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 shown 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.

Published in:

Autonomous Mental Development, IEEE Transactions on  (Volume:1 ,  Issue: 3 )

Date of Publication:

Oct. 2009

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