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Mastering the game of Go without human knowledge
David Silver ,
Julian Schrittwieser ,
Karen Simonyan ,
Ioannis Antonoglou ,
Aja Huang ,
Arthur Guez ,
Thomas Hubert ,
Lucas Baker ,
Matthew Lai ,
Adrian Bolton ,
Yutian Chen ,
Timothy Lillicrap ,
Fan Hui ,
Laurent Sifre ,
George van den Driessche ,
Thore Graepel ,
Demis Hassabis
October 18 2017
October 18 2017
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Abstract
A long-standing goal of artificial intelligence is an algorithm that learns, tabula rasa, superhuman proficiency in challenging domains. Recently, AlphaGo became the first program to defeat a world champion in the game of Go. The tree search in AlphaGo evaluated positions and selected moves
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Most cited references13
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Taking the Human Out of the Loop: A Review of Bayesian Optimization
Bobak Shahriari, Kevin Swersky, Ziyu Wang … (2016)
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Reinforcement learning in robotics: A survey
J. Kober, J. Bagnell, J. Peters (2013)
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A Survey of Monte Carlo Tree Search Methods
Cameron B. Browne, Edward Powley, Daniel Whitehouse … (2012)
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