Reinforcement Learning pdf epub mobi txt 电子书 下载 2025
- 机器学习
- 强化学习
- 人工智能
- AI
- Reinforcement
- 计算机科学
- 增强学习
- 计算机
- Reinforcement Learning
- Machine Learning
- Deep Learning
- Agreement Policy
- State Action Pair
- Reward Function
- Value Iteration
- QLearning
- Offline Learning
具体描述
Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.
作者简介
目录信息
读后感
可以在线阅读，还不错的 我还没仔细读，先把网址公布出来，大家一起学习 http://webdocs.cs.ualberta.ca/~sutton/book/ebook/the-book.html
评分http://incompleteideas.net/book/the-book-2nd.html 有 第二版的 PDF(http://incompleteideas.net/book/bookdraft2018jan1.pdf) ，还有 Python 实现(https://github.com/ShangtongZhang/reinforcement-learning-an-introduction)。
评分http://incompleteideas.net/book/the-book-2nd.html 有 第二版的 PDF(http://incompleteideas.net/book/bookdraft2018jan1.pdf) ，还有 Python 实现(https://github.com/ShangtongZhang/reinforcement-learning-an-introduction)。
评分可以在线阅读，还不错的 我还没仔细读，先把网址公布出来，大家一起学习 http://webdocs.cs.ualberta.ca/~sutton/book/ebook/the-book.html
评分可以在线阅读，还不错的 我还没仔细读，先把网址公布出来，大家一起学习 http://webdocs.cs.ualberta.ca/~sutton/book/ebook/the-book.html
用户评价
入门必读，可结合david silver 的视频课程看
评分介绍性较强,实用性不够,是把整个RL历史和所有的算法都介绍了一遍,但实际上Q-learning已经占据统治地位,前面的两章算是铺垫. 要看实际的例子和代码还是去看 AI- modern approach.
评分读的是second edition draft
评分介绍性较强,实用性不够,是把整个RL历史和所有的算法都介绍了一遍,但实际上Q-learning已经占据统治地位,前面的两章算是铺垫. 要看实际的例子和代码还是去看 AI- modern approach.
评分港真，RL我是先看优酷上David Sliver的视频，然后再看的这书，虽然相比其他的书确实深入浅出的多，但是无奈我英文差，前后花了2个月的下班和周末看完，却一点感觉都没有，搞得我都开始怀疑起自己的智商了，不过话说回来，这确实算是好书，第一次英文原文吸收知识感觉懂了一部分的书。
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