REINFORCEMENT LEARNING AN INTRODUCTION
SUTTON S RICHARD
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.
Computer Science
978-0-262-19398-6
COMPUTER SCIENCE
ENGINEERING
--R23
006.31 SUT
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.
Computer Science
978-0-262-19398-6
COMPUTER SCIENCE
ENGINEERING
--R23
006.31 SUT