LEADER 06127cam 2200253 a 450

001 175125

003 OCoLC

005 20110830074025.0

008 091009s2011 si a b 000 0 eng d

020 $a9789814291347 (hbk.)

020 $a981429134X (hbk.)

035 $a00210523

050 4$aQ335$b.S55 2011

082 04$a006.3$222

090 $a006.3/Sh61///UM042803

100 1 $aShi, Zhongzhi.$3315838

245 10$aAdvanced artificial intelligence /$cZhongzhi Shi.

260 $aSingapore :$bWorld Scientific,$cc2011.

300 $axvi, 613 p. :$bill. ;$c26 cm.

490 1 $aSeries on intelligence science ;$vv. 1

504 $aIncludes bibliographical references (p. 585-613).

505 00$gMachine generated contents note:$gch. 1$tIntroduction --$g1.1.$tBrief History of AI --$g1.2.$tCognitive Issues of AI --$g1.3.$tHierarchical Model of Thought --$g1.4.$tSymbolic Intelligence --$g1.5.$tResearch Approaches of Artificial Intelligence --$g1.6.$tAutomated Reasoning --$g1.7.$tMachine Learning --$g1.8.$tDistributed Artificial Intelligence --$g1.9.$tArtificial Thought Model --$g1.10.$tKnowledge Based Systems --$tExercises --$gch. 2$tLogic Foundation of Artificial Intelligence --$g2.1.$tIntroduction --$g2.2.$tLogic Programming --$g2.3.$tNonmonotonic Logic --$g2.4.$tClosed World Assumption --$g2.5.$tDefault Logic --$g2.6.$tCircumscription Logic --$g2.7.$tNonmonotonic Logic NML --$g2.8.$tAutoepistemic Logic --$g2.9.$tTruth Maintenance System --$g2.10.$tSituation Calculus --$g2.11.$tFrame Problem --$g2.12.$tDynamic Description Logic --$tExercises --$gch. 3$tConstraint Reasoning --$g3.1.$tIntroduction --$g3.2.$tBacktracking --$g3.3.$tConstraint Propagation --$g3.4.$tConstraint Propagation in Tree Search --$g3.5.$tIntelligent Backtracking and Truth Maintenance

505 00$g3.6.$tVariable Instantiation Ordering and Assignment Ordering --$g3.7.$tLocal Revision Search --$g3.8.$tGraph-based Backjumping --$g3.9.$tInfluence-based Backjumping --$g3.10.$tConstraint Relation Processing --$g3.11.$tConstraint Reasoning System COPS --$g3.12.$tILOG Solver --$tExercise --$gch. 4$tQualitative Reasoning --$g4.1.$tIntroduction --$g4.2.$tBasic approaches in qualitative reasoning --$g4.3.$tQualitative Model --$g4.4.$tQualitative Process --$g4.5.$tQualitative Simulation Reasoning --$g4.6.$tAlgebra Approach --$g4.7.$tSpatial Geometric Qualitative Reasoning --$tExercises --$gch. 5$tCase-Based Reasoning --$g5.1.$tOverview --$g5.2.$tBasic Notations --$g5.3.$tProcess Model --$g5.4.$tCase Representation --$g5.5.$tCase Indexing --$g5.6.$tCase Retrieval --$g5.7.$tSimilarity Relations in CBR --$g5.8.$tCase Reuse --$g5.9.$tCase Retainion --$g5.10.$tInstance-Based Learning --$g5.11.$tForecast System for Central Fishing Ground --$tExercises --$gch. 6$tProbabilistic Reasoning --$g6.1.$tIntroduction --$g6.2.$tFoundation of Bayesian Probability --$g6.3.$tBayesian Problem Solving --$g6.4.$tNaive Bayesian Learning Model

505 00$g6.5.$tConstruction of Bayesian Network --$g6.6.$tBayesian Latent Semantic Model --$g6.7.$tSemi-supervised Text Mining Algorithms --$tExercises --$gch. 7$tInductive Learning --$g7.1.$tIntroduction --$g7.2.$tLogic Foundation of Inductive Learning --$g7.3.$tInductive Bias --$g7.4.$tVersion Space --$g7.5.$tAQ Algorithm for Inductive Learning --$g7.6.$tConstructing Decision Trees --$g7.7.$tID3 Learning Algorithm --$g7.8.$tBias Shift Based Decision Tree Algorithm --$g7.9.$tComputational Theories of Inductive Learning --$tExercises --$gch. 8$tSupport Vector Machine --$g8.1.$tStatistical Learning Problem --$g8.2.$tConsistency of Learning Processes --$g8.3.$tStructural Risk Minimization Inductive Principle --$g8.4.$tSupport Vector Machine --$g8.5.$tKernel Function --$tExercises --$gch. 9$tExplanation-Based Learning --$g9.1.$tIntroduction --$g9.2.$tModel for EBL --$g9.3.$tExplanation-Based Generalization --$g9.4.$tExplanation Generalization using Global Substitutions --$g9.5.$tExplanation-Based Specialization --$g9.6.$tLogic Program of Explanation-Based Generalization --$g9.7.$tSOAR Based on Memory Chunks

505 00$g9.8.$tOperationalization --$g9.9.$tEBL with imperfect domain theory --$tExercises --$gch. 10$tReinforcement Learning --$g10.1.$tIntroduction --$g10.2.$tReinforcement Learning Model --$g10.3.$tDynamic Programming --$g10.4.$tMonte Carlo Methods --$g10.5.$tTemporal-Difference Learning --$g10.6.$tQ-Learning --$g10.7.$tFunction Approximation --$g10.8.$tReinforcement Learning Applications --$tExercises --$gch. 11$tRough Set --$g11.1.$tIntroduction --$g11.2.$tReduction of Knowledge --$g11.3.$tDecision Logic --$g11.4.$tReduction of Decision Tables --$g11.5.$tExtended Model of Rough Sets --$g11.6.$tExperimental Systems of Rough Sets --$g11.7.$tGranular Computing --$g11.8.$tFuture Trends of Rough Set Theory --$tExercises --$gch. 12$tAssociation Rules --$g12.1.$tIntroduction --$g12.2.$tThe Apriori Algorithm --$g12.3.$tFP-Growth Algorithm --$g12.4.$tCFP-Tree Algorithm --$g12.5.$tMining General Fuzzy Association Rules --$g12.6.$tDistributed Mining Algorithm For Association Rules --$g12.7.$tParallel Mining of Association Rules --$tExercises --$gch. 13$tEvolutionary Computation --$g13.1.$tIntroduction --$g13.2.$tFormal Model of Evolution System Theory

505 00$g13.3.$tDarwin's Evolutionary Algorithm --$g13.4.$tClassifier System --$g13.5.$tBucket Brigade Algorithm --$g13.6.$tGenetic Algorithm --$g13.7.$tParallel Genetic Algorithm --$g13.8.$tClassifier System Boole --$g13.9.$tRule Discovery System --$g13.10.$tEvolutionary Strategy --$g13.11.$tEvolutionary Programming --$tExercises --$gch. 14$tDistributed Intelligence --$g14.1.$tIntroduction --$g14.2.$tThe Essence of Agent --$g14.3.$tAgent Architecture --$g14.4.$tAgent Communication Language ACL --$g14.5.$tCoordination and Cooperation --$g14.6.$tMobile Agent --$g14.7.$tMulti-Agent Environment MAGE --$g14.8.$tAgent Grid Intelligence Platform --$tExercises --$gch. 15$tArtificial Life --$g15.1.$tIntroduction --$g15.2.$tExploration of Artificial Life --$g15.3.$tArtificial Life Model --$g15.4.$tResearch Approach of Artificial Life --$g15.5.$tCellular Automata --$g15.6.$tMorphogenesis Theory --$g15.7.$tChaos Theories --$g15.8.$tExperimental Systems of Artificial Life --$tExercises.

650 0$aArtificial intelligence.$3154206

830 0$aSeries on intelligence science ;$vv. 1.$3315839