A probabilistic alternative to regression suites
Theoretical Computer Science
Statistical feature combination for the evaluation of game positions
Journal of Artificial Intelligence Research
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A system based on artificial evolution of neural networks for developing new game playing strategies is presented. The system uses marker-based genes to encode nodes in a neural network. The game-playing networks were forced to evolve sophisticated strategies in Othello to compete first with a random mover and then with an alpha-beta search program. Without any direction, the networks discovered first the standard positional strategy, and subsequently the mobility strategy, an advanced strategy rarely seen outside of tournaments. The latter discovery demonstrates how evolution can develop novel solutions by turning an initial disadvantage into an advantage in a changed environment.