Advances in Reinforcement Learning
Mellouk, Abdelhamid
Advances in Reinforcement Learning - IntechOpen 2011 - 1 electronic resource (484 p.)
Open Access
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.
Creative Commons
English
557 9789533073699 9789535155034
10.5772/557 doi
Artificial intelligence
Machine learning
Advances in Reinforcement Learning - IntechOpen 2011 - 1 electronic resource (484 p.)
Open Access
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.
Creative Commons
English
557 9789533073699 9789535155034
10.5772/557 doi
Artificial intelligence
Machine learning