Reinforcement Learning: An Introduction

by Richard S. Sutton and Andrew G. Barto

Introduction
Here you will find the computational examples (with Matlab code) that duplicate the results presented in various sections from this famous book. Please email me if you find anything in error or unclear. Enjoy!

• Chapter 2 (Evaluative Feedback)
  
• Chapter 3 (The Reinforcement Learning Problem)
  
• Chapter 4 (Dynamic Programming)
  
• Chapter 5 (Monte Carlo Methods)
  
• Chapter 6 (Temporal Difference Learning)
  
• Chapter 7 (Eligibility Traces)
  
• Chapter 8 (Generailzation and Function Approximation)
  
• Chapter 9 (Planning and Learning)