TY - GEN
T1 - DeepChess
T2 - 25th International Conference on Artificial Neural Networks and Machine Learning, ICANN 2016
AU - David, Omid E.
AU - Netanyahu, Nathan S.
AU - Wolf, Lior
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2016.
PY - 2016
Y1 - 2016
N2 - We present an end-to-end learning method for chess, relying on deep neural networks. Without any a priori knowledge, in particular without any knowledge regarding the rules of chess, a deep neural network is trained using a combination of unsupervised pretraining and supervised training. The unsupervised training extracts high level features from a given position, and the supervised training learns to compare two chess positions and select the more favorable one. The training relies entirely on datasets of several million chess games, and no further domain specific knowledge is incorporated. The experiments show that the resulting neural network (referred to as DeepChess) is on a par with state-of-the-art chess playing programs, which have been developed through many years of manual feature selection and tuning. DeepChess is the first end-to-end machine learningbased method that results in a grandmaster-level chess playing performance.
AB - We present an end-to-end learning method for chess, relying on deep neural networks. Without any a priori knowledge, in particular without any knowledge regarding the rules of chess, a deep neural network is trained using a combination of unsupervised pretraining and supervised training. The unsupervised training extracts high level features from a given position, and the supervised training learns to compare two chess positions and select the more favorable one. The training relies entirely on datasets of several million chess games, and no further domain specific knowledge is incorporated. The experiments show that the resulting neural network (referred to as DeepChess) is on a par with state-of-the-art chess playing programs, which have been developed through many years of manual feature selection and tuning. DeepChess is the first end-to-end machine learningbased method that results in a grandmaster-level chess playing performance.
UR - http://www.scopus.com/inward/record.url?scp=84988418847&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-44781-0_11
DO - 10.1007/978-3-319-44781-0_11
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AN - SCOPUS:84988418847
SN - 9783319447803
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 88
EP - 96
BT - Artificial Neural Networks and Machine Learning - 25th International Conference on Artificial Neural Networks, ICANN 2016, Proceedings
A2 - Villa, Alessandro E.P.
A2 - Masulli, Paolo
A2 - Rivero, Antonio Javier Pons
PB - Springer Verlag
Y2 - 6 September 2016 through 9 September 2016
ER -