If you have any confusion about the code or want to report a bug, please open an issue instead of emailing me directly, and unfortunately I do not have exercise answers for the book.

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 ...

This book provides the reader with a starting point for understanding the topic. Although written at a research level it provides a comprehensive and accessible introduction to deep reinforcement ...

Reinforcement Learning -- An Introduction 是强化学习思想的经典书籍，非常适合搭建理论基础。 原书英文版第二版于2018年出版，可以从官方网站下载书籍的英文版PDF 下载链接。对于众多中文读者来说，中文官方翻译版这次来得非常及时，《强化学习》 中文版于2019年9月 ...

This paper surveys the field of reinforcement learning from a computer-science perspective. It is written to be accessible to researchers familiar with machine learning. Both the historical basis of ...

Learning from interaction is a foundational idea underlying nearly all theories of learning and intelligence." "Reinforcement learning is learning what to do---how to map situations to actions---so as ...

Students will be expected to be proficient programmers. Reinforcement Learning: An Introduction. By Richard S. Sutton and Andrew G. Barto. MIT Press, Cambridge, MA, 1998. Note that the book is ...

The Reinforcement Learning Specialization by Martha White and Adam White from Coursera covers a significant part of this book. The course is mostly based on the book "Reinforcement Learning: An ...

and reinforcement learning, in addition to design of experiments and evaluation. Students also receive an introduction to philosophical fundamental problems and ethical questions related to ML/AI, as ...