Mastering the game of Go without human knowledge : Nature : Nature Research

Article by · 19 octobre 2017 ·

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

Affiliations Contributions Corresponding author Nature 550, 354–359 (19 October 2017) doi:10.1038/nature24270 Received 07 April 2017 Accepted 13 September 2017 Published online 18 October 2017

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 using deep neural networks. These neural networks were trained by supervised learning from human expert moves, and by reinforcement learning from self-play. (…)

Source : Mastering the game of Go without human knowledge : Nature : Nature Research

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