LEADER 04683nam 22006732 450 001 9910456188103321 005 20151005020621.0 010 $a1-107-13315-7 010 $a0-521-15390-5 010 $a1-280-43403-1 010 $a9786610434039 010 $a0-511-17772-0 010 $a0-511-14812-7 010 $a0-511-30516-8 010 $a0-511-54693-9 010 $a0-511-04544-1 035 $a(CKB)111086906277592 035 $a(EBL)202213 035 $a(OCoLC)559270354 035 $a(SSID)ssj0000227850 035 $a(PQKBManifestationID)11198548 035 $a(PQKBTitleCode)TC0000227850 035 $a(PQKBWorkID)10269419 035 $a(PQKB)10536179 035 $a(UkCbUP)CR9780511546938 035 $a(MiAaPQ)EBC202213 035 $a(Au-PeEL)EBL202213 035 $a(CaPaEBR)ebr10021919 035 $a(CaONFJC)MIL43403 035 $a(EXLCZ)99111086906277592 100 $a20090508d2002|||| uy| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aProbabilistic reasoning in multiagent systems $ea graphical models approach /$fYang Xiang$b[electronic resource] 210 1$aCambridge :$cCambridge University Press,$d2002. 215 $a1 online resource (xii, 294 pages) $cdigital, PDF file(s) 300 $aTitle from publisher's bibliographic system (viewed on 05 Oct 2015). 311 $a0-511-02074-0 311 $a0-521-81308-5 320 $aIncludes bibliographical references (p. 287-291) and index. 327 $tIntelligent Agents --$tReasoning about the Environment --$tWhy Uncertain Reasoning? --$tMultiagent Systems --$tCooperative Multiagent Probabilistic Reasoning --$tApplication Domains --$tBayesian Networks --$tBasics on Bayesian Probability Theory --$tBelief Updating Using JPD --$tGraphs --$tLocal Computation and Message Passing --$tMessage Passing over Multiple Networks --$tApproximation with Massive Message Passing --$tBelief Updating and Cluster Graphs --$tConventions for Message Passing in Cluster Graphs --$tRelation with [lambda] -- [pi] Message Passing --$tMessage Passing in Nondegenerate Cycles --$tMessage Passing in Degenerate Cycles --$tJunction Trees --$tJunction Tree Representation --$tGraphical Separation --$tSufficient Message and Independence --$tEncoding Independence in Graphs --$tJunction Trees and Chordal Graphs --$tTriangulation by Elimination --$tJunction Trees as I-maps --$tJunction Tree Construction --$tBelief Updating with Junction Trees --$tAlgebraic Properties of Potentials --$tPotential Assignment in Junction Trees --$tPassing Belief over Separators --$tPassing Belief through a Junction Tree --$tProcessing Observations --$tMultiply Sectioned Bayesian Networks --$tThe Task of Distributed Uncertain Reasoning --$tOrganization of Agents during Communication --$tAgent Interface --$tMultiagent Dependence Structure --$tLinked Junction Forests --$tMultiagent Distributed Compilation of MSBNs --$tMultiagent Moralization of MSDAG --$tEffective Communication Using Linkage Trees --$tLinkage Trees as I-maps --$tMultiagent Triangulation. 330 $aThis 2002 book investigates the opportunities in building intelligent decision support systems offered by multi-agent distributed probabilistic reasoning. Probabilistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become increasingly an active field of research and practice in artificial intelligence, operations research and statistics. The success of this technique in modeling intelligent decision support systems under the centralized and single-agent paradigm has been striking. Yang Xiang extends graphical dependence models to the distributed and multi-agent paradigm. He identifies the major technical challenges involved in such an endeavor and presents the results. The framework developed in the book allows distributed representation of uncertain knowledge on a large and complex environment embedded in multiple cooperative agents, and effective, exact and distributed probabilistic inference. 606 $aDistributed artificial intelligence 606 $aBayesian statistical decision theory$xData processing 606 $aMultiagent systems 615 0$aDistributed artificial intelligence. 615 0$aBayesian statistical decision theory$xData processing. 615 0$aMultiagent systems. 676 $a006.3 700 $aXiang$b Yang$f1954-$01046786 801 0$bUkCbUP 801 1$bUkCbUP 906 $aBOOK 912 $a9910456188103321 996 $aProbabilistic reasoning in multiagent systems$92473973 997 $aUNINA