Abstract
The predator/prey domain is utilized to conduct research in Distributed Artificial Intelligence. Genetic Programming is used to evolve behavioral strategies for the predator agents. To further the utility of the predator strategies, the prey population is allowed to evolve at the same time. The expected competitive learning cycle did not surface. This failing is investigated, and a simple prey algorithm surfaces, which is consistently able to evade capture from the predator algorithms.
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© 1996 Springer-Verlag Berlin Heidelberg
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Haynes, T., Sen, S. (1996). Evolving behavioral strategies in predators and prey. In: Weiß, G., Sen, S. (eds) Adaption and Learning in Multi-Agent Systems. IJCAI 1995. Lecture Notes in Computer Science, vol 1042. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60923-7_22
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DOI: https://doi.org/10.1007/3-540-60923-7_22
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