Recent Advances in Reinforcement Learning (Hardcover, Reprinted from MACHINE LEARNING 22:1-3, 1996)

Recent Advances in Reinforcement Learning addresses current research in an exciting area that is gaining a great deal of popularity in the Artificial Intelligence and Neural Network communities. Reinforcement learning has become a primary paradigm of machine learning. It applies to problems in which an agent (such as a robot, a process controller, or an information-retrieval engine) has to learn how to behave given only information about the success of its current actions. This book is a collection of important papers that address topics including the theoretical foundations of dynamic programming approaches, the role of prior knowledge, and methods for improving performance of reinforcement-learning techniques. These papers build on previous work and will form an important resource for students and researchers in the area. Recent Advances in Reinforcement Learning is an edited volume of peer-reviewed original research comprising twelve invited contributions by leading researchers. This research work has also been published as a special issue of Machine Learning (Volume 22, Numbers 1, 2 and 3).

General

Imprint:	Springer
Country of origin:	Netherlands
Release date:	2001
First published:	1996
Editors:	Leslie Pack Kaelbling
Dimensions:	235 x 155 x 17mm (L x W x T)
Format:	Hardcover
Pages:	292
Edition:	Reprinted from MACHINE LEARNING 22:1-3, 1996
ISBN-13:	978-0-7923-9705-2
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Promotions
LSN:	0-7923-9705-3
Barcode:	9780792397052

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