Emergence of competitive and cooperative behavior using coevolution

Authors:
Padmini Rajagopalan;Aditya Rawal;Risto Miikkulainen
Affiliations:
University of Texas at Austin, Austin, TX, USA;University of Texas at Austin, Austin, TX, USA;University of Texas at Austin, Austin, TX, USA
Venue:
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Year:
2010

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Abstract

In nature there are teams of collaborators and competitors that evolve at the same time, yet computationally they have mostly been studied separately so far. This paper focuses on simultaneous cooperative and competitive coevolution in a complex predator-prey domain. Yong and Miikkulainen's [6] Multi-Agent ESP architecture is extended to a Multi-Component ESP architecture consisting of multiple cooperating neural networks within an agent. This architecture successfully demonstrates hierarchical cooperation and competition in teams of prey and predators. In sustained coevolution in this complex domain, high-level pursuit-evasion behaviors emerge. In this manner, coevolution of neural networks is shown to scale up to an arms race of multiple competing and cooperating populations, more closely modeling coevolution in nature.