“增强学习-入门导读”版本间的差异
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（→AlphaGo计算机围棋） |
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===<B>AlphaGo计算机围棋</B>=== | ===<B>AlphaGo计算机围棋</B>=== | ||
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| + | 蒙特卡洛树搜索（Monte-Carlo tree search） | ||
:Bandit based monte-carlo planning, ecml 2006. | :Bandit based monte-carlo planning, ecml 2006. | ||
| 第16行： | 第18行： | ||
:Combining Online and Offline Knowledge in UCT, ICML 2007. | :Combining Online and Offline Knowledge in UCT, ICML 2007. | ||
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| + | *Monte-Carlo tree search and rapid action value estimation in computer Go, artificial intelligence, Elsevier 2011. | ||
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| + | 神经网络 | ||
:Mimicking Go Experts with Convolutional Neural Networks, ICANN 2008. | :Mimicking Go Experts with Convolutional Neural Networks, ICANN 2008. | ||
| − | * | + | *Training Deep Convolutional Neural Networks to Play Go, icml 2015. |
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| + | 进展 | ||
| + | :Achieving Master Level Play in 9 × 9 Computer Go, AAAI 2008. | ||
:The grand challenge of computer Go Monte Carlo tree search and extensions, cacm 2012. | :The grand challenge of computer Go Monte Carlo tree search and extensions, cacm 2012. | ||
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*Mastering the game of Go with deep neural networks and tree search, nature 2016. | *Mastering the game of Go with deep neural networks and tree search, nature 2016. | ||
2017年1月17日 (二) 01:36的版本
增强学习入门
教材
增强学习 or 强化学习经典教材
- An Introduction to Reinforcement Learning Intro_RL
- Algorithms for Reinforcement Learning RLAlgsInMDPs
研究
AlphaGo计算机围棋
蒙特卡洛树搜索（Monte-Carlo tree search）
- Bandit based monte-carlo planning, ecml 2006.
- Efficient Selectivity and Backup Operators in Monte-Carlo Tree Search, CG 2006.
- Combining Online and Offline Knowledge in UCT, ICML 2007.
- Monte-Carlo tree search and rapid action value estimation in computer Go, artificial intelligence, Elsevier 2011.
神经网络
- Mimicking Go Experts with Convolutional Neural Networks, ICANN 2008.
- Training Deep Convolutional Neural Networks to Play Go, icml 2015.
进展
- Achieving Master Level Play in 9 × 9 Computer Go, AAAI 2008.
- The grand challenge of computer Go Monte Carlo tree search and extensions, cacm 2012.
- Mastering the game of Go with deep neural networks and tree search, nature 2016.
