Reinforcement Learning by Richard S Sutton

Reinforcement Learning by Richard S Sutton

Reinforcement learning is the learning of a mapping from situations to actions so as to maximize a scalar reward or reinforcement signal. The learner is not told which action to take, as in most forms of machine learning, but instead must discover which actions yield the highest reward by trying them. In the most interesting and challenging cases, actions may affect not only the immediate reward, but also the next situation, and through that all subsequent rewards. These two characteristics -- trial-and-error search and delayed reward -- are the most important distinguishing features of reinforcement learning. Reinforcement learning is both a new and a very old topic in AI. The term appears to have been coined by Minsk (1961), and independently in control theory by Walz and Fu (1965). The earliest machine learning research now viewed as directly relevant was Samuel's (1959) checker player, which used temporal-difference learning to manage delayed reward much as it is used today. Of course learning and reinforcement have been studied in psychology for almost a century, and that work has had a very strong impact on the AI/engineering work. One could in fact consider all of reinforcement learning to be simply the reverse engineering of certain psychological learning processes (e.g. operant conditioning and secondary reinforcement). Reinforcement Learning is an edited volume of original research, comprising seven invited contributions by leading researchers.

S. Richard Richard S. Richard S. Richard S. Richard Sutton is Distinguished Research Scientist at DeepMind and Professor of Computer Science and AITF Chair in Reinforcement Learning and Artificial Intelligence at the University of Alberta.

SKU	Unavailable
ISBN 13	9781461366089
ISBN 10	1461366089
Title	Reinforcement Learning
Author	Richard S Sutton
Series	The Springer International Series In Engineering And Computer Science
Condition	Unavailable
Binding Type	Paperback
Publisher	Springer-Verlag New York Inc.
Year published	2012-10-08
Number of pages	172
Cover note	Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
Note	Unavailable