Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1126/science.aar6404 |
A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play | |
Silver, David1,2; Hubert, Thomas1; Schrittwieser, Julian1; Antonoglou, Ioannis1; Lai, Matthew1; Guez, Arthur1; Lanctot, Marc1; Sifre, Laurent1; Kumaran, Dharshan1; Graepel, Thore1; Lillicrap, Timothy1; Simonyan, Karen1; Hassabis, Demis1 | |
2018-12-07 | |
发表期刊 | SCIENCE
![]() |
ISSN | 0036-8075 |
EISSN | 1095-9203 |
出版年 | 2018 |
卷号 | 362期号:6419页码:1140-+ |
文章类型 | Article |
语种 | 英语 |
国家 | England |
英文摘要 | The game of chess is the longest-studied domain in the history of artificial intelligence. The strongest programs are based on a combination of sophisticated search techniques, domain-specific adaptations, and handcrafted evaluation functions that have been refined by human experts over several decades. By contrast, the AlphaGo Zero program recently achieved superhuman performance in the game of Go by reinforcement learning from self-play. In this paper, we generalize this approach into a single AlphaZero algorithm that can achieve superhuman performance in many challenging games. Starting from random play and given no domain knowledge except the game rules, AlphaZero convincingly defeated a world champion program in the games of chess and shogi (Japanese chess), as well as Go. |
领域 | 地球科学 ; 气候变化 ; 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000452506300053 |
WOS关键词 | GAME |
WOS类目 | Multidisciplinary Sciences |
WOS研究方向 | Science & Technology - Other Topics |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/200250 |
专题 | 地球科学 资源环境科学 气候变化 |
作者单位 | 1.DeepMind, 6 Pancras Sq, London N1C 4AG, England; 2.UCL, Gower St, London WC1E 6BT, England |
推荐引用方式 GB/T 7714 | Silver, David,Hubert, Thomas,Schrittwieser, Julian,et al. A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play[J]. SCIENCE,2018,362(6419):1140-+. |
APA | Silver, David.,Hubert, Thomas.,Schrittwieser, Julian.,Antonoglou, Ioannis.,Lai, Matthew.,...&Hassabis, Demis.(2018).A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play.SCIENCE,362(6419),1140-+. |
MLA | Silver, David,et al."A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play".SCIENCE 362.6419(2018):1140-+. |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论