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Observing the Evolution of Neural Networks Learning to Play the Game of Othello
2005
IEEE Transactions on Evolutionary Computation
A study was conducted to find out how game-playing strategies for Othello (also known as reversi) can be learned without expert knowledge. The approach used the coevolution of a fixed-architecture neural-network-based evaluation function combined with a standard minimax search algorithm. Comparisons between evolving neural networks and computer players that used deterministic strategies allowed evolution to be observed in real-time. Neural networks evolved to outperform the computer players
doi:10.1109/tevc.2005.843750
fatcat:6yyun5j34fe7bcwdilqbgn4264