“第三十一章 围棋国手”版本间的差异
来自cslt Wiki
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* DeepMind AlphaGO [https://www.deepmind.com/research/highlighted-research/alphago] | * DeepMind AlphaGO [https://www.deepmind.com/research/highlighted-research/alphago] | ||
* 百度百科:AlphaGo [https://baike.baidu.com/item/%E9%98%BF%E5%B0%94%E6%B3%95%E5%9B%B4%E6%A3%8B/19319610] | * 百度百科:AlphaGo [https://baike.baidu.com/item/%E9%98%BF%E5%B0%94%E6%B3%95%E5%9B%B4%E6%A3%8B/19319610] | ||
| + | * 维基百科:Alpha Go [http://aigraph.cslt.org/courses/31/AlphaGo-zh.pdf][http://aigraph.cslt.org/courses/31/AlphaGo.pdf] | ||
| + | * 薛永红, 王洪鹏, 机器下棋的历史与启示——从“深蓝”到AlphaZero [http://html.rhhz.net/kjdb/20191913.htm] | ||
| + | * AlphaGo赢得首场人机对决奇点离人更近了？ [https://m.21jingji.com/article/20160310/c699786ad54b0a23d9b5f4d448d2e33f.html] | ||
* Reconstructing Turing's "Paper Machine" [https://en.chessbase.com/post/reconstructing-turing-s-paper-machine] | * Reconstructing Turing's "Paper Machine" [https://en.chessbase.com/post/reconstructing-turing-s-paper-machine] | ||
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==高级读者== | ==高级读者== | ||
| − | * | + | * Silver D, Schrittwieser J, Simonyan K, et al. Mastering the game of go without human knowledge[J]. nature, 2017, 550(7676): 354-359. [https://discovery.ucl.ac.uk/id/eprint/10045895/1/agz_unformatted_nature.pdf] |
| − | * | + | * Schrittwieser J, Antonoglou I, Hubert T, et al. Mastering atari, go, chess and shogi by planning with a learned model[J]. Nature, 2020, 588(7839): 604-609.[https://arxiv.org/pdf/1911.08265.pdf&lang=en] |
2022年8月13日 (六) 04:23的版本
教学资料
扩展阅读
- AI100问：阿尔法狗和深蓝算法有什么不同？ [2]
- AI100问：AlphaZero是如何从零学习的？ Zero是如何从零学习的.pdf
- AI100问：alphago是如何战胜人类的？ [3]
- DeepMind AlphaGO [4]
- 百度百科:AlphaGo [5]
- 维基百科:Alpha Go [6][7]
- 薛永红, 王洪鹏, 机器下棋的历史与启示——从“深蓝”到AlphaZero [8]
- AlphaGo赢得首场人机对决奇点离人更近了？ [9]
- Reconstructing Turing's "Paper Machine" [10]
视频展示
- 图灵的象棋程序[11]
