- Category: Computer
- Author: Richard S. Sutton and Andrew G. Barto
- License: CC BY-NC-ND 2.0
- Pages: : 522 pages
- File type: : PDF (548 pages)
Read and download free eBook intituled Reinforcement Learning: An Introduction, Second Edition in format : PDF (548 pages) – : 522 pages created by Richard S. Sutton and Andrew G. Barto.
Reinforcement Learning (RL), 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 while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field’s key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics.
Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. The treatment to be accessible to readers in all of the related disciplines.
Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning.
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