02913nam 2200685 a 450 991083011560332120210715085735.01-118-62010-01-118-55742-51-299-31547-X1-118-61987-0(CKB)2560000000100628(EBL)1143625(SSID)ssj0000833610(PQKBManifestationID)11529302(PQKBTitleCode)TC0000833610(PQKBWorkID)10936259(PQKB)10364510(MiAaPQ)EBC1143625(OCoLC)830161640(CaSebORM)9781118620106(EXLCZ)99256000000010062820091207d2010 uy 0engur|n|---|||||txtrdacontentcrdamediacrrdacarrierMarkov decision processes in artificial intelligence MDPs, beyond MDPs and applications /edited by Olivier Sigaud, Olivier BuffetLondon ISTE[2010]1 online resource (457 pages)First published 2008 in France by Hermes Science/Lavoisier in two volumes entitled: Processus décisionnels de Markov en intelligence artificielle.1-84821-167-8 Includes bibliographical references and index.pt. 1. MDPs : models and methods -- pt. 2. Beyond MDPs -- pt. 3. Applications.Markov Decision Processes (MDPs) are a mathematical framework for modeling sequential decision problems under uncertainty as well as Reinforcement Learning problems. Written by experts in the field, this book provides a global view of current research using MDPs in Artificial Intelligence. It starts with an introductory presentation of the fundamental aspects of MDPs (planning in MDPs, Reinforcement Learning, Partially Observable MDPs, Markov games and the use of non-classical criteria). Then it presents more advanced research trends in the domain and gives some concrete examples using illustrSafari tech books online.Wiley UBCM ebooks.ISTEArtificial intelligenceMathematicsArtificial intelligenceStatistical methodsMarkov processesStatistical decisionArtificial intelligenceMathematics.Artificial intelligenceStatistical methods.Markov processes.Statistical decision.006.301/509233006.301509233006.33Sigaud Olivier564768Sigaud Olivier564768Buffet Olivier953653MiAaPQMiAaPQMiAaPQBOOK9910830115603321Markov decision processes in artificial intelligence2156329UNINA