增强学习-入门导读

增强学习入门

教材

增强学习 or 强化学习经典教材

1. Richard S. Sutton, Andrew Barto, An Introduction to Reinforcement Learning, MIT Press, 1998.

Intro_RL

1. Csaba Szepesvari, Algorithms for Reinforcement Learning, Synthesis lectures on artificial intelligence and machine learning 4, no. 1 (2010): 1-103. 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.