Computer and Information Science » Artificial Intelligence

Advances in Reinforcement Learning

Edited by Abdelhamid Mellouk, ISBN 978-953-307-369-9, 470 pages, Publisher: InTech, Chapters published January 14, 2011 under CC BY-NC-SA 3.0 license
DOI: 10.5772/557

Reinforcement Learning (RL) is a very dynamic area in terms of theory and application. This book brings together many different aspects of the current research on several fields associated to RL which has been growing rapidly, producing a wide variety of learning algorithms for different applications. Based on 24 Chapters, it covers a very broad variety of topics in RL and their application in autonomous systems. A set of chapters in this book provide a general overview of RL while other chapters focus mostly on the applications of RL paradigms: Game Theory, Multi-Agent Theory, Robotic, Networking Technologies, Vehicular Navigation, Medicine and Industrial Logistic.