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2012472620 contributor B12636192.
2012472620 created "c2011.".
2012472620 date "2011".
2012472620 date "c2011.".
2012472620 dateCopyrighted "c2011.".
2012472620 description "13.3. Darwin's Evolutionary Algorithm -- 13.4. Classifier System -- 13.5. Bucket Brigade Algorithm -- 13.6. Genetic Algorithm -- 13.7. Parallel Genetic Algorithm -- 13.8. Classifier System Boole -- 13.9. Rule Discovery System -- 13.10. Evolutionary Strategy -- 13.11. Evolutionary Programming -- Exercises -- ch. 14 Distributed Intelligence -- 14.1. Introduction -- 14.2. The Essence of Agent -- 14.3. Agent Architecture -- 14.4. Agent Communication Language ACL -- 14.5. Coordination and Cooperation -- 14.6. Mobile Agent -- 14.7. Multi-Agent Environment MAGE -- 14.8. Agent Grid Intelligence Platform -- Exercises -- ch. 15 Artificial Life -- 15.1. Introduction -- 15.2. Exploration of Artificial Life -- 15.3. Artificial Life Model -- 15.4. Research Approach of Artificial Life -- 15.5. Cellular Automata -- 15.6. Morphogenesis Theory -- 15.7. Chaos Theories -- 15.8. Experimental Systems of Artificial Life -- Exercises.".
2012472620 description "3.6. Variable Instantiation Ordering and Assignment Ordering -- 3.7. Local Revision Search -- 3.8. Graph-based Backjumping -- 3.9. Influence-based Backjumping -- 3.10. Constraint Relation Processing -- 3.11. Constraint Reasoning System COPS -- 3.12. ILOG Solver -- Exercise -- ch. 4 Qualitative Reasoning -- 4.1. Introduction -- 4.2. Basic approaches in qualitative reasoning -- 4.3. Qualitative Model -- 4.4. Qualitative Process -- 4.5. Qualitative Simulation Reasoning -- 4.6. Algebra Approach -- 4.7. Spatial Geometric Qualitative Reasoning -- Exercises -- ch. 5 Case-Based Reasoning -- 5.1. Overview -- 5.2. Basic Notations -- 5.3. Process Model -- 5.4. Case Representation -- 5.5. Case Indexing -- 5.6. Case Retrieval -- 5.7. Similarity Relations in CBR -- 5.8. Case Reuse -- 5.9. Case Retainion -- 5.10. Instance-Based Learning -- 5.11. Forecast System for Central Fishing Ground -- Exercises -- ch. 6 Probabilistic Reasoning -- 6.1. Introduction -- 6.2. Foundation of Bayesian Probability -- 6.3. Bayesian Problem Solving -- 6.4. Naive Bayesian Learning Model".
2012472620 description "6.5. Construction of Bayesian Network -- 6.6. Bayesian Latent Semantic Model -- 6.7. Semi-supervised Text Mining Algorithms -- Exercises -- ch. 7 Inductive Learning -- 7.1. Introduction -- 7.2. Logic Foundation of Inductive Learning -- 7.3. Inductive Bias -- 7.4. Version Space -- 7.5. AQ Algorithm for Inductive Learning -- 7.6. Constructing Decision Trees -- 7.7. ID3 Learning Algorithm -- 7.8. Bias Shift Based Decision Tree Algorithm -- 7.9. Computational Theories of Inductive Learning -- Exercises -- ch. 8 Support Vector Machine -- 8.1. Statistical Learning Problem -- 8.2. Consistency of Learning Processes -- 8.3. Structural Risk Minimization Inductive Principle -- 8.4. Support Vector Machine -- 8.5. Kernel Function -- Exercises -- ch. 9 Explanation-Based Learning -- 9.1. Introduction -- 9.2. Model for EBL -- 9.3. Explanation-Based Generalization -- 9.4. Explanation Generalization using Global Substitutions -- 9.5. Explanation-Based Specialization -- 9.6. Logic Program of Explanation-Based Generalization -- 9.7. SOAR Based on Memory Chunks".
2012472620 description "9.8. Operationalization -- 9.9. EBL with imperfect domain theory -- Exercises -- ch. 10 Reinforcement Learning -- 10.1. Introduction -- 10.2. Reinforcement Learning Model -- 10.3. Dynamic Programming -- 10.4. Monte Carlo Methods -- 10.5. Temporal-Difference Learning -- 10.6. Q-Learning -- 10.7. Function Approximation -- 10.8. Reinforcement Learning Applications -- Exercises -- ch. 11 Rough Set -- 11.1. Introduction -- 11.2. Reduction of Knowledge -- 11.3. Decision Logic -- 11.4. Reduction of Decision Tables -- 11.5. Extended Model of Rough Sets -- 11.6. Experimental Systems of Rough Sets -- 11.7. Granular Computing -- 11.8. Future Trends of Rough Set Theory -- Exercises -- ch. 12 Association Rules -- 12.1. Introduction -- 12.2. The Apriori Algorithm -- 12.3. FP-Growth Algorithm -- 12.4. CFP-Tree Algorithm -- 12.5. Mining General Fuzzy Association Rules -- 12.6. Distributed Mining Algorithm For Association Rules -- 12.7. Parallel Mining of Association Rules -- Exercises -- ch. 13 Evolutionary Computation -- 13.1. Introduction -- 13.2. Formal Model of Evolution System Theory".
2012472620 description "Includes bibliographical references (p. 585-613).".
2012472620 description "Machine generated contents note: ch. 1 Introduction -- 1.1. Brief History of AI -- 1.2. Cognitive Issues of AI -- 1.3. Hierarchical Model of Thought -- 1.4. Symbolic Intelligence -- 1.5. Research Approaches of Artificial Intelligence -- 1.6. Automated Reasoning -- 1.7. Machine Learning -- 1.8. Distributed Artificial Intelligence -- 1.9. Artificial Thought Model -- 1.10. Knowledge Based Systems -- Exercises -- ch. 2 Logic Foundation of Artificial Intelligence -- 2.1. Introduction -- 2.2. Logic Programming -- 2.3. Nonmonotonic Logic -- 2.4. Closed World Assumption -- 2.5. Default Logic -- 2.6. Circumscription Logic -- 2.7. Nonmonotonic Logic NML -- 2.8. Autoepistemic Logic -- 2.9. Truth Maintenance System -- 2.10. Situation Calculus -- 2.11. Frame Problem -- 2.12. Dynamic Description Logic -- Exercises -- ch. 3 Constraint Reasoning -- 3.1. Introduction -- 3.2. Backtracking -- 3.3. Constraint Propagation -- 3.4. Constraint Propagation in Tree Search -- 3.5. Intelligent Backtracking and Truth Maintenance".
2012472620 extent "xvi, 613 p. :".
2012472620 identifier "9789814291347".
2012472620 identifier "981429134X".
2012472620 isPartOf "Series on intelligence science ; v. 1".
2012472620 isPartOf "Series on intelligence science ; v. 1.".
2012472620 issued "2011".
2012472620 issued "c2011.".
2012472620 language "eng".
2012472620 publisher "Singapore ; Hackensack, NJ : World Scientific,".
2012472620 subject "006.3 22".
2012472620 subject "Artificial intelligence.".
2012472620 subject "Intelligence artificielle. ram".
2012472620 subject "Q335 .S4668 2011".
2012472620 tableOfContents "13.3. Darwin's Evolutionary Algorithm -- 13.4. Classifier System -- 13.5. Bucket Brigade Algorithm -- 13.6. Genetic Algorithm -- 13.7. Parallel Genetic Algorithm -- 13.8. Classifier System Boole -- 13.9. Rule Discovery System -- 13.10. Evolutionary Strategy -- 13.11. Evolutionary Programming -- Exercises -- ch. 14 Distributed Intelligence -- 14.1. Introduction -- 14.2. The Essence of Agent -- 14.3. Agent Architecture -- 14.4. Agent Communication Language ACL -- 14.5. Coordination and Cooperation -- 14.6. Mobile Agent -- 14.7. Multi-Agent Environment MAGE -- 14.8. Agent Grid Intelligence Platform -- Exercises -- ch. 15 Artificial Life -- 15.1. Introduction -- 15.2. Exploration of Artificial Life -- 15.3. Artificial Life Model -- 15.4. Research Approach of Artificial Life -- 15.5. Cellular Automata -- 15.6. Morphogenesis Theory -- 15.7. Chaos Theories -- 15.8. Experimental Systems of Artificial Life -- Exercises.".
2012472620 tableOfContents "3.6. Variable Instantiation Ordering and Assignment Ordering -- 3.7. Local Revision Search -- 3.8. Graph-based Backjumping -- 3.9. Influence-based Backjumping -- 3.10. Constraint Relation Processing -- 3.11. Constraint Reasoning System COPS -- 3.12. ILOG Solver -- Exercise -- ch. 4 Qualitative Reasoning -- 4.1. Introduction -- 4.2. Basic approaches in qualitative reasoning -- 4.3. Qualitative Model -- 4.4. Qualitative Process -- 4.5. Qualitative Simulation Reasoning -- 4.6. Algebra Approach -- 4.7. Spatial Geometric Qualitative Reasoning -- Exercises -- ch. 5 Case-Based Reasoning -- 5.1. Overview -- 5.2. Basic Notations -- 5.3. Process Model -- 5.4. Case Representation -- 5.5. Case Indexing -- 5.6. Case Retrieval -- 5.7. Similarity Relations in CBR -- 5.8. Case Reuse -- 5.9. Case Retainion -- 5.10. Instance-Based Learning -- 5.11. Forecast System for Central Fishing Ground -- Exercises -- ch. 6 Probabilistic Reasoning -- 6.1. Introduction -- 6.2. Foundation of Bayesian Probability -- 6.3. Bayesian Problem Solving -- 6.4. Naive Bayesian Learning Model".
2012472620 tableOfContents "6.5. Construction of Bayesian Network -- 6.6. Bayesian Latent Semantic Model -- 6.7. Semi-supervised Text Mining Algorithms -- Exercises -- ch. 7 Inductive Learning -- 7.1. Introduction -- 7.2. Logic Foundation of Inductive Learning -- 7.3. Inductive Bias -- 7.4. Version Space -- 7.5. AQ Algorithm for Inductive Learning -- 7.6. Constructing Decision Trees -- 7.7. ID3 Learning Algorithm -- 7.8. Bias Shift Based Decision Tree Algorithm -- 7.9. Computational Theories of Inductive Learning -- Exercises -- ch. 8 Support Vector Machine -- 8.1. Statistical Learning Problem -- 8.2. Consistency of Learning Processes -- 8.3. Structural Risk Minimization Inductive Principle -- 8.4. Support Vector Machine -- 8.5. Kernel Function -- Exercises -- ch. 9 Explanation-Based Learning -- 9.1. Introduction -- 9.2. Model for EBL -- 9.3. Explanation-Based Generalization -- 9.4. Explanation Generalization using Global Substitutions -- 9.5. Explanation-Based Specialization -- 9.6. Logic Program of Explanation-Based Generalization -- 9.7. SOAR Based on Memory Chunks".
2012472620 tableOfContents "9.8. Operationalization -- 9.9. EBL with imperfect domain theory -- Exercises -- ch. 10 Reinforcement Learning -- 10.1. Introduction -- 10.2. Reinforcement Learning Model -- 10.3. Dynamic Programming -- 10.4. Monte Carlo Methods -- 10.5. Temporal-Difference Learning -- 10.6. Q-Learning -- 10.7. Function Approximation -- 10.8. Reinforcement Learning Applications -- Exercises -- ch. 11 Rough Set -- 11.1. Introduction -- 11.2. Reduction of Knowledge -- 11.3. Decision Logic -- 11.4. Reduction of Decision Tables -- 11.5. Extended Model of Rough Sets -- 11.6. Experimental Systems of Rough Sets -- 11.7. Granular Computing -- 11.8. Future Trends of Rough Set Theory -- Exercises -- ch. 12 Association Rules -- 12.1. Introduction -- 12.2. The Apriori Algorithm -- 12.3. FP-Growth Algorithm -- 12.4. CFP-Tree Algorithm -- 12.5. Mining General Fuzzy Association Rules -- 12.6. Distributed Mining Algorithm For Association Rules -- 12.7. Parallel Mining of Association Rules -- Exercises -- ch. 13 Evolutionary Computation -- 13.1. Introduction -- 13.2. Formal Model of Evolution System Theory".
2012472620 tableOfContents "Machine generated contents note: ch. 1 Introduction -- 1.1. Brief History of AI -- 1.2. Cognitive Issues of AI -- 1.3. Hierarchical Model of Thought -- 1.4. Symbolic Intelligence -- 1.5. Research Approaches of Artificial Intelligence -- 1.6. Automated Reasoning -- 1.7. Machine Learning -- 1.8. Distributed Artificial Intelligence -- 1.9. Artificial Thought Model -- 1.10. Knowledge Based Systems -- Exercises -- ch. 2 Logic Foundation of Artificial Intelligence -- 2.1. Introduction -- 2.2. Logic Programming -- 2.3. Nonmonotonic Logic -- 2.4. Closed World Assumption -- 2.5. Default Logic -- 2.6. Circumscription Logic -- 2.7. Nonmonotonic Logic NML -- 2.8. Autoepistemic Logic -- 2.9. Truth Maintenance System -- 2.10. Situation Calculus -- 2.11. Frame Problem -- 2.12. Dynamic Description Logic -- Exercises -- ch. 3 Constraint Reasoning -- 3.1. Introduction -- 3.2. Backtracking -- 3.3. Constraint Propagation -- 3.4. Constraint Propagation in Tree Search -- 3.5. Intelligent Backtracking and Truth Maintenance".
2012472620 title "Advanced artificial intelligence / Zhongzhi Shi.".
2012472620 type "text".