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David E. Moriarty

58 bytes added, 10:38, 15 July 2020
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For Go and Othello, the input layer sees the board configuration, while the output layer indicates the goodness of each possible move by an output neuron associated with each space or point of the board.
However the research was conducted a few years before the [[Monte-Carlo Tree Search|MCTS]] revolution appeared in computer Go, not to mention the [[Deep Learning|deep learning]] breakthrough.
The [[Pruning|forward pruning]] decisions of In the [[Alpha-Beta|alpha-beta]] search in of the Othello was controlled by experiment, the neural network [[Move Ordering|orders the moves]], and further controls whether moves are [[Pruning|pruned forward]] <ref>[[David E. Moriarty]], [[Risto Miikkulainen]] ('''1994'''). ''[http://nn.cs.utexas.edu/?moriarty:aaai94 Evolving Neural Networks to focus Minimax Search]''. [[Conferences#AAAI-94|AAAI-94]]</ref>.
=Selected Publications=
Retrieved from "https://www.chessprogramming.org/Special:MobileDiff/20205"

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