REINFORCEMENT LEARNING AN INTRODUCTION
- SECOND EDITION
- LONDON THE MIT PRESS 2018
- XIX 526P
OPTIMIZATION & AUTOMATION
"Reinforcement Learning: An Introduction" by Richard S. Sutton and Andrew G. Barto is a fundamental textbook detailing how an agent learns optimal decisions by interacting with an environment to maximize a reward signal. The book covers core concepts such as agents, environments, policies, reward signals, and value functions, and explores methods like Dynamic Programming, Monte Carlo, and Temporal-Difference learning.