LEADER 00877nam0-2200313---450- 001 990009747330403321 005 20130618125339.0 010 $a0522838952 035 $a000974733 035 $aFED01000974733 035 $a(Aleph)000974733FED01 035 $a000974733 100 $a20130618d1969----km-y0itay50------ba 101 0 $aeng 102 $aAU 105 $ay-------001yy 200 1 $aCellular immunology$fMacfarlane Burnet 210 $aCarlton$cMelbourne University press$d1969 215 $aVIII, 725 p., [4] c. di tav.$cill.$d22 cm 300 $aSul front. Books one and two 610 0 $aImmunologia 700 1$aBurnet,$bF. M.$g$0508165 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990009747330403321 952 $aStanza 1.53$fDMVPA 959 $aDMVPA 996 $aCellular immunology$9833771 997 $aUNINA LEADER 02689nam 22006015 450 001 9910633910303321 005 20251204103902.0 010 $a9783031076145 010 $a3031076141 024 7 $a10.1007/978-3-031-07614-5 035 $a(MiAaPQ)EBC7151652 035 $a(Au-PeEL)EBL7151652 035 $a(CKB)25554151900041 035 $a(PPN)267814003 035 $a(OCoLC)1356006549 035 $a(DE-He213)978-3-031-07614-5 035 $a(EXLCZ)9925554151900041 100 $a20221202d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDecision Making Under Uncertainty and Reinforcement Learning $eTheory and Algorithms /$fby Christos Dimitrakakis, Ronald Ortner 205 $a1st ed. 2022. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (251 pages) 225 1 $aIntelligent Systems Reference Library,$x1868-4408 ;$v223 311 08$a9783031076121 311 08$a3031076125 320 $aIncludes bibliographical references and index. 327 $aIntroduction -- Subjective probability and utility -- Decision problems -- Estimation. . 330 $aThis book presents recent research in decision making under uncertainty, in particular reinforcement learning and learning with expert advice. The core elements of decision theory, Markov decision processes and reinforcement learning have not been previously collected in a concise volume. Our aim with this book was to provide a solid theoretical foundation with elementary proofs of the most important theorems in the field, all collected in one place, and not typically found in introductory textbooks. This book is addressed to graduate students that are interested in statistical decision making under uncertainty and the foundations of reinforcement learning. . 410 0$aIntelligent Systems Reference Library,$x1868-4408 ;$v223 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aComputational Intelligence 606 $aArtificial Intelligence 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 676 $a658.403 676 $a658.4033 700 $aDimitrakakis$b Christos$01271036 702 $aOrtner$b Ronald 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910633910303321 996 $aDecision Making under Uncertainty and Reinforcement Learning$92994364 997 $aUNINA