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| Preface | |
| Acknowledgements | |
| Overview of Knowledge Acquisition and Learning | p. 1 |
| Overviews | p. 5 |
| Toward a unified theory of learning: Multistrategy task-adaptive learning | p. 7 |
| A survey of knowledge acquisition techniques and tools | p. 39 |
| Expertise and Expert Systems | p. 57 |
| Expertise and Its Acquisition | p. 59 |
| Development of expertise | p. 61 |
| Modeling expert knowledge | p. 78 |
| KADS: A modelling approach to knowledge engineering | p. 92 |
| Knowledge acquisition for expert systems: Some pitfalls and suggestions | p. 117 |
| Expert Systems and Generic Problem Classes | p. 125 |
| Fundamentals of expert systems | p. 127 |
| Preliminary steps toward a taxonomy of problem-solving methods | p. 149 |
| Generic tasks in knowledge-based reasoning: High-level building blocks for expert system design | p. 170 |
| Acquiring, representing, and evaluating a competence model of diagnostic strategy | p. 178 |
| Interactive Elicitation Tools | p. 217 |
| Eliciting Classification Knowledge | p. 219 |
| Interactive transfer of expertise: Acquisition of new inference rules | p. 221 |
| Expertise transfer and complex problems: Using AQUINAS as a knowledge-acquisition workbench for knowledge-based systems | p. 240 |
| MOLE: A tenacious knowledge-acquisition tool | p. 253 |
| Eliciting Design Knowledge | p. 261 |
| SALT: A knowledge acquisition language for propose-and-revise systems | p. 263 |
| Automated support for building and extending expert models | p. 282 |
| Automated knowledge acquisition for strategic knowledge | p. 297 |
| Inductive Generalization Methods | p. 319 |
| Learning Classification Knowledge | p. 321 |
| A theory and methodology of inductive learning | p. 323 |
| Induction of decision trees | p. 349 |
| Connectionist learning procedures | p. 362 |
| Automatic knowledge base refinement for classification systems | p. 387 |
| Learning Classes Via Clustering | p. 403 |
| Models of incremental concept formation | p. 405 |
| Autoclass: A Bayesian classification system | p. 431 |
| Measurement and Evaluation of Learning Systems | p. 443 |
| Symbolic and neural learning algorithms: An experimental comparison | p. 445 |
| The quantification of knowledge: Formal foundations for knowledge acquisition methodologies | p. 462 |
| Limitations on inductive learning | p. 475 |
| Compilation and Deep Models | p. 481 |
| Compilation of Knowledge for Efficiency | p. 483 |
| Learning and executing generalized robot plans | p. 485 |
| Learning by experimentation: Acquiring and refining problem-solving heuristics | p. 504 |
| Chunking in SOAR: The anatomy of a general learning mechanism | p. 518 |
| Explanation-Based Learning | p. 537 |
| Explanation-based generalization: A unifying view | p. 539 |
| Explanation generalization in EGGS | p. 556 |
| Synthesizing Problem Solvers from Deep Models | p. 577 |
| XPLAIN: A system for creating and explaining expert consulting programs | p. 579 |
| Domain-specific automatic programming | p. 600 |
| Qualitative modelling and learning in KARDIO | p. 616 |
| Apprenticeship Learning Systems | p. 627 |
| Apprentice Systems for Classification Knowledge | p. 629 |
| Knowledge base refinement as improving an incomplete and incorrect domain theory | p. 631 |
| Apprentice Systems for Design Knowledge | p. 643 |
| LEAP: A learning apprentice for VLSI design | p. 645 |
| Techniques of design and DISCIPLE learning apprentice | p. 655 |
| Analogical and Case-based Reasoning | p. 669 |
| Analogical Reasoning | p. 671 |
| The mechanisms of analogical learning | p. 673 |
| The structure-mapping engine: Algorithm and examples | p. 695 |
| Derivational analogy: A theory of reconstructive problem solving and expertise acquisition | p. 727 |
| Case-Based Reasoning | p. 739 |
| Concept learning and heuristic classification in weak-theory domains | p. 741 |
| Improving rule-based systems through case-based reasoning | p. 759 |
| Explaining and repairing plans that fail | p. 765 |
| Discovery and Commonsense Knowledge | p. 793 |
| Discovery Systems | p. 795 |
| The ubiquity of discovery | p. 797 |
| Classifier systems and genetic algorithms | p. 812 |
| Commonsense Knowledge | p. 837 |
| CYC: A midterm report | p. 839 |
| Appendix A: Use of the Book in a Course | p. 867 |
| Appendix B: Guide to the Literature | p. 871 |
| Appendix C: Addendum to Chapter 2 | p. 879 |
| Bibliography | p. 887 |
| Author Index | p. 889 |
| Subject Index | p. 899 |
| Table of Contents provided by Blackwell. All Rights Reserved. |
Readings in Knowledge Acquisition and Learning
by Buchanan, Bruce G.; Wilkins, David C.Format: Paperback
Pub. Date: 1992-12-01
Publisher(s): Morgan Kaufmann Pub
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