Reinforcement Learning: An Introduction(2nd)阅读笔记

Rich Sutton的强化学习，有能力者请阅读英文原版。

目录

• Part I

  • Chapter 1: Introduction
  • Chapter 2: Multi-armed Bandits
  • Chapter 3: Finite Markov Decision Processes
  • Chapter 4: Dynamic Programming
  • Chapter 5: Monte Carlo Methods
  • Chapter 6: Temporal-Difference Learning
  • Chapter 7: n-step Bootstrapping
  • Chapter 8: Planning and Learning with Tabular Methods

• Part II

  • Chapter 9: On-policy Prediction with Approximation
  • Chapter 10: On-policy Control with Approximation
  • Chapter 11: Off-policy Methods with Approximation
  • Chapter 12: Eligibility Traces
  • Chapter 13: Policy Gradient Methods

• Part III

  • Chapter 14: Psychology
  • Chapter 15: Neuroscience
  • Chapter 16: Applications and Case Studies

链接

英文原版地址：http://incompleteideas.net/book/the-book-2nd.html

Google Drive资料：https://drive.google.com/drive/folders/0B3w765rOKuKANmxNbXdwaE1YU1k