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010   $a3-319-28929-2
024 7 $a10.1007/978-3-319-28929-8
035   $a(CKB)3710000000718245
035   $a(EBL)4537987
035   $a(DE-He213)978-3-319-28929-8
035   $a(MiAaPQ)EBC4537987
035   $a(PPN)194380351
035   $a(EXLCZ)993710000000718245
100   $a20160603d2016      u|         0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 12$aA Concise Introduction to Decentralized POMDPs /$fby Frans A. Oliehoek, Christopher Amato
205   $a1st ed. 2016.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016.
215   $a1 online resource (146 p.)
225 1 $aSpringerBriefs in Intelligent Systems, Artificial Intelligence, Multiagent Systems, and Cognitive Robotics,$x2196-548X
300   $aDescription based upon print version of record.
311   $a3-319-28927-6 
320   $aIncludes bibliographical references.
327   $aMultiagent Systems Under Uncertainty -- The Decentralized POMDP Framework -- Finite-Horizon Dec-POMDPs -- Exact Finite-Horizon Planning Methods -- Approximate and Heuristic Finite-Horizon Planning Methods -- Infinite-Horizon Dec-POMDPs -- Infinite-Horizon Planning Methods: Discounted Cumulative Reward -- Infinite-Horizon Planning Methods: Average Reward -- Further Topics.
330   $aThis book introduces multiagent planning under uncertainty as formalized by decentralized partially observable Markov decision processes (Dec-POMDPs). The intended audience is researchers and graduate students working in the fields of artificial intelligence related to sequential decision making: reinforcement learning, decision-theoretic planning for single agents, classical multiagent planning, decentralized control, and operations research. .
410  0$aSpringerBriefs in Intelligent Systems, Artificial Intelligence, Multiagent Systems, and Cognitive Robotics,$x2196-548X
606   $aArtificial intelligence
606   $aControl engineering
606   $aRobotics
606   $aMechatronics
606   $aMathematical optimization
606   $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000
606   $aControl, Robotics, Mechatronics$3https://scigraph.springernature.com/ontologies/product-market-codes/T19000
606   $aOptimization$3https://scigraph.springernature.com/ontologies/product-market-codes/M26008
615  0$aArtificial intelligence.
615  0$aControl engineering.
615  0$aRobotics.
615  0$aMechatronics.
615  0$aMathematical optimization.
615 14$aArtificial Intelligence.
615 24$aControl, Robotics, Mechatronics.
615 24$aOptimization.
676   $a658.403
700   $aOliehoek$b Frans A$4aut$4http://id.loc.gov/vocabulary/relators/aut$0950734
702   $aAmato$b Christopher$4aut$4http://id.loc.gov/vocabulary/relators/aut
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910255017203321
996   $aA Concise Introduction to Decentralized POMDPs$92149537
997   $aUNINA