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Biasing Coevolutionary Search for Optimal Multiagent Behaviors
2006
IEEE Transactions on Evolutionary Computation
Cooperative coevolutionary algorithms offer great potential for concurrent multiagent learning domains and are of special utility to domains involving teams of multiple agents. Unfortunately, they also exhibit pathologies resulting from their game-theoretic nature, and these pathologies interfere with finding solutions that correspond to optimal collaborations of interacting agents. We address this problem by biasing a cooperative coevolutionary algorithm in such a way that the fitness of an
doi:10.1109/tevc.2006.880330
fatcat:5a7c7tukr5eu5atx2jxl6d7wpm