Abstract
We describe a hybrid Artificial Intelligence (AI) approach combining soft AI techniques (neural networks) and hard AI methods (alpha-beta game tree search), in an attempt to approximate human play more accurately, in particular with reference to the game of Go. The program is tested and analysed by play against another Go playing program and it is shown that the use of hard AI enhances the performance of the soft AI system and vice-versa.
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