Second Generation Expert Systems have been a very activefield of research during the last years. Much work has beencarried out to overcome drawbacks of first generation expertsystems. This book presents an overview and newcontributions from people who have played a major role inthis evolution. It is divided in several sections that coverthe main topics of the subject:- Combining Multiple Reasoning Paradigms- Knowledge Level Modelling- Knowledge Acquisition in Second Generation Expert Systems- Explanation of Reasoning- Architectures for Second Generation Expert Systems.This book can serve as a…mehr
Second Generation Expert Systems have been a very activefield of research during the last years. Much work has beencarried out to overcome drawbacks of first generation expertsystems. This book presents an overview and newcontributions from people who have played a major role inthis evolution. It is divided in several sections that coverthe main topics of the subject:- Combining Multiple Reasoning Paradigms- Knowledge Level Modelling- Knowledge Acquisition in Second Generation Expert Systems- Explanation of Reasoning- Architectures for Second Generation Expert Systems.This book can serve as a reference book for researchers andstudents and will also be an invaluable help forpractitioners involved in KBS developments.
I: Introduction.- 1. Second Generation Expert Systems: A Step Forward in Knowledge Engineering.- II: Combining Multiple Models & Reasoning Techniques.- 2. The Roles of Knowledge Representation in Problem Solving.- 3. Combining Heuristic Reasoning with Causal Reasoningin Diagnostic Problem Solving.- 4. Combining Causal Models and Case-Based Reasoning.- 5. Generate, Test and Debug: A Paradigm for Combining Associational and Causal Reasoning.- 6. The Business Analyzer: A Second Generation Approach to Financial Decision Support.- 7. QUAWDS: Diagnosis Using Different Models for Different Subtasks.- 8. Integrating Functional Models and Structural Domain Models for Diagnostic Applications.- 9. Multiple Models for Emergency Planning.- 10. Knowledge-Based Design Using the Multi-Modeling Approach.- III: Knowledge Level Approaches.- 11. Issues in Knowledge Level Modelling.- 12. Generic Tasks and Task Structures: History, Critique and New Directions.- 13. The Componential Framework and its Role in Reusability.- 14. Towards a Unification of Knowledge Modelling Approaches.- 15. On the Relationship between Knowledge-based Systems Theory and Application Programs: Leveraging Task Specific Approaches.- 16. Generic Models and their Support in Modeling Problem Solving Behavior.- 17. Building and Maintaining a Large Knowledge-Based System from a 'Knowledge Level1 Perspective: the DIVA Experiment.- IV: Knowledge Acquisition.- 18. An Overview of Knowledge Acquisition.- 19. Knowledge Acquisition Process Support Through Generalised Directive Models.- 20. Using the System-Model-Operator Metaphor for Knowledge Acquisition.- 21. Explicit and operational models as a basis for second generation knowledge acquisition tools.- 22. ACTE: A Causal Model-Based Knowledge Acquisition Tool.- 23. Acquisition and Validation of Expert Knowledge by Using Causal Models.- V: Explanation.- 24. Explanation in Second Generation Expert Systems.- 25. Explanation Using Task Structure and Domain Functional Models.- 26. Second Generation Expert System Explanation.- VI: Architectures.- 27. Architectural Foundations for Real-Time Performance in Intelligent Agents.- 28. An Investigation of the Roles of Problem-Solving Methods in Diagnosis.- 29. Knowledge Architectures for Real Time Decision Support.- 30. MODEL-K for prototyping and strategic reasoning at the knowledge level.- 31. A Framework for Integrating Heterogeneous Learning Agents.
I: Introduction.- 1. Second Generation Expert Systems: A Step Forward in Knowledge Engineering.- II: Combining Multiple Models & Reasoning Techniques.- 2. The Roles of Knowledge Representation in Problem Solving.- 3. Combining Heuristic Reasoning with Causal Reasoningin Diagnostic Problem Solving.- 4. Combining Causal Models and Case-Based Reasoning.- 5. Generate, Test and Debug: A Paradigm for Combining Associational and Causal Reasoning.- 6. The Business Analyzer: A Second Generation Approach to Financial Decision Support.- 7. QUAWDS: Diagnosis Using Different Models for Different Subtasks.- 8. Integrating Functional Models and Structural Domain Models for Diagnostic Applications.- 9. Multiple Models for Emergency Planning.- 10. Knowledge-Based Design Using the Multi-Modeling Approach.- III: Knowledge Level Approaches.- 11. Issues in Knowledge Level Modelling.- 12. Generic Tasks and Task Structures: History, Critique and New Directions.- 13. The Componential Framework and its Role in Reusability.- 14. Towards a Unification of Knowledge Modelling Approaches.- 15. On the Relationship between Knowledge-based Systems Theory and Application Programs: Leveraging Task Specific Approaches.- 16. Generic Models and their Support in Modeling Problem Solving Behavior.- 17. Building and Maintaining a Large Knowledge-Based System from a 'Knowledge Level1 Perspective: the DIVA Experiment.- IV: Knowledge Acquisition.- 18. An Overview of Knowledge Acquisition.- 19. Knowledge Acquisition Process Support Through Generalised Directive Models.- 20. Using the System-Model-Operator Metaphor for Knowledge Acquisition.- 21. Explicit and operational models as a basis for second generation knowledge acquisition tools.- 22. ACTE: A Causal Model-Based Knowledge Acquisition Tool.- 23. Acquisition and Validation of Expert Knowledge by Using Causal Models.- V: Explanation.- 24. Explanation in Second Generation Expert Systems.- 25. Explanation Using Task Structure and Domain Functional Models.- 26. Second Generation Expert System Explanation.- VI: Architectures.- 27. Architectural Foundations for Real-Time Performance in Intelligent Agents.- 28. An Investigation of the Roles of Problem-Solving Methods in Diagnosis.- 29. Knowledge Architectures for Real Time Decision Support.- 30. MODEL-K for prototyping and strategic reasoning at the knowledge level.- 31. A Framework for Integrating Heterogeneous Learning Agents.
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