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A Coevolutionary Model for The Virus Game
2006
2006 IEEE Symposium on Computational Intelligence and Games
In this paper, coevolution is used to evolve Artificial Neural Networks (ANN) which evaluate board positions of a two player zero-sum game (The Virus Game). The coevolved neural networks play at a level that beats a group of strong hand-crafted AI players. We investigate the performance of coevolution starting from random initial weights and starting with weights that are tuned by gradient based adaptive learning methods (Backpropagation, RPROP and iRPROP). The results of coevolutionary
doi:10.1109/cig.2006.311680
dblp:conf/cig/CowlingNH06
fatcat:ww4ulouaufdu7ljclyahnrpewe