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dc.contributor.editorMellouk, Abdelhamid
dc.date.accessioned2021-04-20T15:04:44Z
dc.date.available2021-04-20T15:04:44Z
dc.date.issued2011
dc.identifierONIX_20210420_9789533073699_264
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/64908
dc.description.abstractReinforcement 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.
dc.languageEnglish
dc.subject.classificationbic Book Industry Communication::U Computing & information technology::UY Computer science::UYQ Artificial intelligenceen_US
dc.subject.otherMachine learning
dc.titleAdvances in Reinforcement Learning
dc.typebook
oapen.identifier.doi10.5772/557
oapen.relation.isPublishedBy78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6
oapen.relation.isbn9789533073699
oapen.relation.isbn9789535155034
oapen.imprintIntechOpen
oapen.pages484


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