Advances in reinforcement learning / / edited by Abdelhamid Mellouk.
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 application...
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| Place / Publishing House: | Rijeka, Croatia : : InTech,, [2011] ©2011 |
| Year of Publication: | 2011 |
| Language: | English |
| Physical Description: | 1 online resource (484 pages) :; illustrations |
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| Summary: | 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. |
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| Bibliography: | Includes bibliographical references. |
| ISBN: | 9535155032 |
| Access: | Open access |
| Hierarchical level: | Monograph |
| Statement of Responsibility: | edited by Abdelhamid Mellouk. |