发信人: saturnV (土星五号), 信区: Programming
标 题: FAIR open sourced ELF OpenGo
发信站: BBS 未名空间站 (Thu May 3 15:06:02 2018, 美东)
Today, Facebook AI Research (FAIR) open sourced ELF OpenGo, an AI bot that
has defeated world champion professional Go players, based on our existing
ELF platform for Reinforcement Learning Research. We are releasing both the
trained model and the code used to create it.
Inspired by DeepMind’s work, we kicked off an effort earlier this year to
reproduce their recent AlphaGoZero results using FAIR’s Extensible,
Lightweight Framework (ELF) for reinforcement learning research. The goal
was to create an open source implementation of a system that would teach
itself how to play Go at the level of a professional human player or better.
By releasing our code and models we hoped to inspire others to think about
new applications and research directions for this technology.
ELF OpenGo has been successful playing against both other open source bots
and human Go players. We played a series of games (198 wins, 2 losses)
against LeelaZero (158603eb, Apr. 25, 2018), the strongest publicly
available bot, using its default settings and no pondering. We also achieved
a 14 win, 0 loss record against four of the top 30 world-ranked human Go
players. These games were all played using a single GPU making moves every
50 seconds, Chinese rules with 7.5 komi, and unlimited time given to human
players to consider their moves.
※ 修改:·saturnV 於 May 3 15:06:28 2018 修改本文·[FROM: 108.]
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