Richard S. Sutton的作品

Richard S. Sutton

Richard S. Sutton is Professor of Computing Science and AITF Chair in Reinforcement Learning and Artificial Intelligence at the University of Alberta, and also Distinguished Research Scientist at DeepMind.

强化学习（第2版）
【加】Richard S. Sutton（理查德·桑顿）
评分 8.4分
《强化学习（第2版）》作为强化学习思想的深度解剖之作，被业内公认为是一本强化学习基础理论的经典著作。它从强化学习的基本思想出发，深入浅出又严谨细致地介绍了马尔可夫决策过程、蒙特卡洛方法、时序差分方法、同轨离轨策略等强化学习的基本概念和方法，并以大量的实例帮助读者理解强化学习的问题建模过程以及核心的算法细节。《强化学习（第2版）》适合所有对强化学习感兴趣的读者阅读、收藏。
Reinforcement Learning (2/e)
Richard S. Sutton, Andrew G. Barto
评分 9.6分
The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the

Richard S. Sutton

Richard S. Sutton is Professor of Computing Science and AITF Chair in Reinforcement Learning and Artificial Intelligence at the University of Alberta, and also Distinguished Research Scientist at DeepMind.

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计算机科学计算机算法机器学习数学强化学习

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电子工业出版社 A Bradford Book