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Markov decision processes in artificial intelligence

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...

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Detalles Bibliográficos
Autores principales: Sigaud, Olivier, Buffet, Olivier
Lenguaje:eng
Publicado: Wiley-ISTE 2013
Materias:
Acceso en línea:http://cds.cern.ch/record/1617136
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author Sigaud, Olivier
Buffet, Olivier
author_facet Sigaud, Olivier
Buffet, Olivier
author_sort Sigaud, Olivier
collection CERN
description 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 illustr
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publishDate 2013
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spelling cern-16171362021-04-21T22:03:20Zhttp://cds.cern.ch/record/1617136engSigaud, OlivierBuffet, OlivierMarkov decision processes in artificial intelligenceMathematical Physics and MathematicsMarkov 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 illustrWiley-ISTEoai:cds.cern.ch:16171362013
spellingShingle Mathematical Physics and Mathematics
Sigaud, Olivier
Buffet, Olivier
Markov decision processes in artificial intelligence
title Markov decision processes in artificial intelligence
title_full Markov decision processes in artificial intelligence
title_fullStr Markov decision processes in artificial intelligence
title_full_unstemmed Markov decision processes in artificial intelligence
title_short Markov decision processes in artificial intelligence
title_sort markov decision processes in artificial intelligence
topic Mathematical Physics and Mathematics
url http://cds.cern.ch/record/1617136
work_keys_str_mv AT sigaudolivier markovdecisionprocessesinartificialintelligence
AT buffetolivier markovdecisionprocessesinartificialintelligence