发表于2025-04-04
Reinforcement Learning 2025 pdf epub mobi 电子书
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
图书标签: 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, 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.
作为一个学渣 看一会就打瞌睡???? 硬着头皮看了一半,终于还是放弃了T-T
评分真觉得这书写的很一般
评分18书2. 太精彩了,这样的书才叫深入浅出。
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.
评分作为一个学渣 看一会就打瞌睡???? 硬着头皮看了一半,终于还是放弃了T-T
Reinforcement Learning 2025 pdf epub mobi 电子书