Advances in reinforcement learning

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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Detalles Bibliográficos
Otros Autores: Mellouk, Abdelhamid (Editor), Mellouk, Abdelhamid, editor (editor)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Rijeka, Croatia : IntechOpen 2011
[2011]
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009653916006719
Descripción
Sumario: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.
Descripción Física:1 online resource (484 pages) : illustrations
Bibliografía:Includes bibliographical references.
ISBN:9789535155034
Acceso:Open access