Deep+Pink

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an experimental open source chess engine by Erik Bernhardsson written in Python as an attempt to learn and play chess. It applies negamax alpha-beta and a deep neural network as evaluation function, using [|Theano], python-chess, and Sunfish. The input representation seems similar to Octavius with 12x64 nodes, not feeding in side to move, castling rights, and en passant target square. The first hidden layer has 2048 neurons as well. Bernhardsson used a GPU instance to train the net with 100M games for about four days using [|stochastic gradient descent] with Nesterov momentum.
 * Deep Pink **,

=See also=
 * Chess Engines with Neural Networks
 * Deep Learning
 * Neural MoveMap Heuristic
 * Octavius

=Postings= > [|As the author of sunfish....] by Thomas Ahle, December 2, 2014 > [|This has been tried many times before, with better-but-still-lackluster results....] by halfcat, [|Hacker News], December 2, 2014
 * [|Deep learning for… chess] by Erik Bernhardsson, November 29, 2014 » Deep Learning
 * [|Deep learning for chess Comments] [|Hacker News]
 * [|Deep learning for… chess (addendum)] by Erik Bernhardsson, December 8, 2014
 * [|ŷhat | Deep Learning for ... Chess] by Erik Bernhardsson, February 02, 2017
 * [|Deep Pink: a chess engine using deep learning] by Chao Ma, CCC, February 05, 2017

=External Links=
 * [|GitHub - erikbern/deep-pink: Deep Pink is a chess AI that learns to play chess using deep learning]

=References= =What links here?= include page="Deep Pink" component="backlinks" limit="20"
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