Doyle / Sandewall / Torasso Principles of Knowledge Representation and Reasoning

Proceedings of the Fourth International Conference (KR '94)
1. Auflage 2014
ISBN: 978-1-4832-1452-8
Verlag: Elsevier Science & Techn.
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 668 Seiten, Web PDF

Principles of Knowledge Representation and Reasoning contains the proceedings of the Fourth International Conference on Principles of Knowledge Representation and Reasoning (KR '94) held in Bonn, Germany, on May 24-27, 1994. The conference provided a forum for reviewing the theory and principles underlying knowledge representation and reasoning. Topics covered range from reasoning about mental states and spatial reasoning with propositional logics to default logic as a query language. Comprised of 60 chapters, this book begins with a description of a formal language for representing and reasoning about time and action before turning to proof in context and how it can replace the most common uses of reflection principles. The reader is then introduced to reasoning with minimal models; belief ascription and mental-level modeling; and a unified framework for class-based representation formalisms. A general approach to specificity in default reasoning is also described, together with an ontology for engineering mathematics and the use of abduction to generate tests. The book concludes by considering the use of natural language for knowledge representation and reasoning. This monograph will be of interest to both students and practitioners in the fields of artificial intelligence and computer science.

Autoren/Hrsg.

Doyle, Jon

Sandewall, Erik

Torasso, Pietro

Inhaltsverzeichnis

1;Front Cover;1
2;Principles of Knowledge Representation and Reasoning;4
3;Copyright Page;5
4;Table of Contents;6
5;Preface;10
6;Acknowledgments;11
7;Part I: Contributed Papers;14
7.1;Chapter 1. A Computational Account for a Description Logic of Time and Action;16
7.1.1;Abstract;16
7.1.2;1 INTRODUCTION;16
7.1.3;2 THE TEMPORAL LANGUAGE;17
7.1.4;3 ACTIONS AND PLANS;20
7.1.5;4 THE CALCULUS;22
7.1.6;5 CONCLUSIONS;26
7.1.7;Acknowledgments;26
7.1.8;References;26
7.2;Chapter 2. Proofs in context;28
7.2.1;Abstract;28
7.2.2;1 INTRODUCTION;28
7.2.3;2 DIFFICULTIES WITH PROOFS IN CONTEXT;29
7.2.4;3 A METHOD FOR PROOFS IN CONTEXT;31
7.2.5;4 A PROOF METHOD AND NOTATION;33
7.2.6;5 CONCLUSIONS;36
7.2.7;Acknowledgments;36
7.2.8;References;36
7.2.9;A APPENDIX;38
7.3;Chapter 3. An Integrated Implementation of Simulative, Uncertain and Metaphorical Reasoning about Mental States;40
7.3.1;Abstract;40
7.3.2;1 INTRODUCTION;40
7.3.3;2 METAPHORS OF MIND;40
7.3.4;3 SKETCH OF REASONING;42
7.3.5;4 REPRESENTATION SCHEME;44
7.3.6;5 REASONING BASICS;45
7.3.7;6 BELIEF REASONING;47
7.3.8;7 METAPHORICAL REASONING;49
7.3.9;8 CONCLUSION;50
7.3.10;Acknowledgements;51
7.3.11;References;51
7.4;Chapter 4. Reasoning with minimal models: Efficient algorithms and applications;52
7.4.1;Abstract;52
7.4.2;1 Introduction;52
7.4.3;2 The elimination algorithm for HCF theories;53
7.4.4;3 The elimination algorithm forfirst-order HCF theories;55
7.4.5;4 Applications of the elimination algorithm;57
7.4.6;5 Expressive power of stratified knowledgebases;60
7.4.7;6 Related work;61
7.4.8;7 Conclusion;61
7.4.9;Appendix;61
7.4.10;Acknowledgments;62
7.4.11;References;62
7.5;Chapter 5. Spatial Reasoning with Propositional Logics;64
7.5.1;Abstract;64
7.5.2;1 INTRODUCTION;64
7.5.3;2 TOPOLOGICAL INTERPRETATION OF PROPOSITIONAL LOGIC;65
7.5.4;3 DEFINING TOPOLOGICAL RELATIONS;66
7.5.5;4 REASONING WITH Co+;68
7.5.6;5 MORE EXPRESSIVENESS WITH INTUITIONISTIC LOGIC;69
7.5.7;6 IMPLEMENTATION OF A20+ REASONING SYSTEM;71
7.5.8;7 EXTENDING THE REPRESENTATION;72
7.5.9;8 CONCLUSIONS;75
7.5.10;Acknowledgements;75
7.5.11;References;75
7.6;Chapter 6. On the Relation Between Default and Modal Consequence Relations;76
7.6.1;Abstract;76
7.6.2;1 INTRODUCTION;76
7.6.3;2 DEFAULT CONSEQUENCE RELATIONS;76
7.6.4;3 MODAL DEFAULT CONSEQUENCE RELATIONS;81
7.6.5;4 REDUCTIONS AND EMBEDDINGS;84
7.6.6;5 CONCLUSIONS;86
7.6.7;References;87
7.7;Chapter 7. Toward a Logic for Qualitative Decision Theory;88
7.7.1;Abstract;88
7.7.2;1 Introduction;88
7.7.3;2 Conditional Preferences;89
7.7.4;3 Default Knowledge;93
7.7.5;4 Ability and Incomplete Knowledge;94
7.7.6;5 Concluding Remarks;98
7.7.7;References;99
7.7.8;Acknowledgements;99
7.8;Chapter 8. Belief Ascription and Mental-level Modelling;100
7.8.1;Abstract;100
7.8.2;1 INTRODUCTION;100
7.8.3;2 THE FRAMEWORK;102
7.8.4;3 ASCRIBING BELIEF;104
7.8.5;4 CHOOSING AMONG BELIEF ASSIGNMENTS;105
7.8.6;5 ADDING TIME;106
7.8.7;6 BELIEF CHANGE;106
7.8.8;7 EXISTENCE - GOAL SEEKING AGENTS;108
7.8.9;8 DISCUSSION;109
7.8.10;Acknowledgement;110
7.8.11;References;111
7.9;Chapter 9. Default Logic as a Query Language;112
7.9.1;Abstract;112
7.9.2;1 INTRODUCTION;112
7.9.3;2 DEFINITION OF DQL;113
7.9.4;3 EXPRESSIVE POWER OF DQL;115
7.9.5;4 APPLICATIONS AND EXAMPLES;118
7.9.6;5 COMBINED COMPLEXITY OF DQL;119
7.9.7;6 CONCLUSIONS;120
7.9.8;APPENDIX;120
7.9.9;Acknowledgements;120
7.9.10;References;120
7.10;Chapter 10. A Unified Framework for Class-Based Representation Formalisms;122
7.10.1;Abstract;122
7.10.2;1 INTRODUCTION;122
7.10.3;2 A UNIFYING CLASS-BASED REPRESENTATION LANGUAGE;123
7.10.4;3 REASONING IN UNRESTRICTED MODELS;128
7.10.5;4 REASONING IN FINITE MODELS;130
7.10.6;5 CONCLUSIONS;132
7.10.7;Acknowledgements;132
7.10.8;References;132
7.11;Chapter 11. Learning the CLASSIC Description Logic: Theoretical and Experimental Results;134
7.11.1;Abstract;134
7.11.2;1 INTRODUCTION;134
7.11.3;2 BACKGROUND;134
7.11.4;3 C-CLASSIC IS PAC-LEARNABLE;138
7.11.5;4 EXPERIMENTAL RESULTS;140
7.11.6;5 LEARNING DISJUNCTIONS;142
7.11.7;6 CONCLUDING REMARKS;145
7.11.8;Acknowledgments;145
7.11.9;References;145
7.12;Chapter 12. Directional Resolution: The Davis-Putnam Procedure, Revisited;147
7.12.1;Abstract;147
7.12.2;1 Introduction;147
7.12.3;2 Definition and preliminaries;148
7.12.4;3 DP-elimination – Directional Resolution;148
7.12.5;4 Tractable classes;149
7.12.6;5 Bounded directional resolution;154
7.12.7;6 Experimental evaluation;154
7.12.8;7 Related work and conclusions;156
7.12.9;Acknowledgements;158
7.12.10;References;158
7.13;Chapter 13. A General Approach to Specificity in Default Reasoning;159
7.13.1;Abstract;159
7.13.2;1 Introduction;159
7.13.3;2 Background;160
7.13.4;3 The Approach: Intuitions;162
7.13.5;4 Minimal Conflicting Sets;164
7.13.6;5 Compiling Specificity into Default Theories;165
7.13.7;6 Alternative Translations;168
7.13.8;7 Discussion;169
7.13.9;Acknowledgements;170
7.13.10;References;170
7.14;Chapter 14. Action Representation for interpreting Purpose Clauses in Natural Language Instructions;171
7.14.1;Abstract;171
7.14.2;1 INTRODUCTION;171
7.14.3;2 INFERENCE PROCESSES;171
7.14.4;3 THE REPRESENTATION FORMALISM;173
7.14.5;4 INFERENCE IMPLEMENTATION;178
7.14.6;5 CONCLUSIONS;181
7.14.7;Acknowledgements;181
7.14.8;References;181
7.15;Chapter 15. Conditional Objects as Nonmonotonic Consequence Relations;183
7.15.1;Abstract;183
7.15.2;1 INTRODUCTION;183
7.15.3;2 CONDITIONAL OBJECTS: THE 3-VALUED SEMANTICS;184
7.15.4;3 CONNECTIVES FOR DEFAULT RULES;185
7.15.5;4 CONDITIONAL OBJECTS AND NONMONOTONIC CONSEQUENCE RELATIONS;186
7.15.6;5 CONSISTENCY AND REFUTATION;187
7.15.7;6 QUASI-CONJUNCTION AND META-RESOLUTION;187
7.15.8;7 TWO MODES OF BELIEF REVISION;188
7.15.9;8 CONCLUSION;188
7.15.10;Acknowledgements;188
7.15.11;ANNEX;188
7.15.12;References;189
7.16;Chapter 16. Tractable Closed World Reasoning with Updates;191
7.16.1;Abstract;191
7.16.2;1 INTRODUCTION AND MOTIVATION;191
7.16.3;2 LOCAL CLOSED WORLD INFORMATION;192
7.16.4;3 UPDATING CLOSED WORLD INFORMATION;194
7.16.5;4 EXPERIMENTAL RESULTS;197
7.16.6;5 RELATED WORK;197
7.16.7;6 FUTURE WORK;198
7.16.8;7 CONCLUSIONS;198
7.16.9;A ACTION SEMANTICS;198
7.16.10;B PROOFS;199
7.16.11;Acknowledgments;200
7.16.12;References;200
7.17;Chapter 17. A Knowledge-Based Framework for Belief Change, Part II: Revision and Update;203
7.17.1;Abstract;203
7.17.2;1 INTRODUCTION;203
7.17.3;2 THE FRAMEWORK;204
7.17.4;3 BELIEF CHANGE SYSTEMS;205
7.17.5;4 REVISION;206
7.17.6;5 UPDATE;208
7.17.7;6 SYNTHESIS;210
7.17.8;7 CONCLUSION;213
7.17.9;Acknowledgements;213
7.17.10;References;213
7.18;Chapter 18. On the Complexity of Conditional Logics;215
7.18.1;Abstract;215
7.18.2;1 INTRODUCTION;215
7.18.3;2 CONDITIONAL LOGIC;217
7.18.4;3 SMALL MODEL THEOREMS;217
7.18.5;4 COMPLEXITY RESULTS;221
7.18.6;5 AXIOMATIZATION;224
7.18.7;6 CONCLUSIONS;225
7.18.8;Acknowledgements;225
7.18.9;References;225
7.19;Chapter 19. An Efficient Method for Managing Disjunctions in Qualitative Temporal Reasoning;227
7.19.1;Abstract;227
7.19.2;1 INTRODUCTION;227
7.19.3;2 MANAGING DISJUNCTIONS THROUGH TIMEGRAPHS;228
7.19.4;3 EXPERIMENTAL RESULTS;235
7.19.5;4 CONCLUSIONS;237
7.19.6;Acknowledgements;237
7.19.7;References;237
7.20;Chapter 20. GSAT and Dynamic Backtracking;239
7.20.1;Abstract;239
7.20.2;1 INTRODUCTION;239
7.20.3;2 CONSTRAINTS AND NOGOODS;240
7.20.4;3 DYNAMIC BACKTRACKING;242
7.20.5;4 DYNAMIC BACKTRACKING AS LOCAL SEARCH;243
7.20.6;5 PARTIAL-ORDER DYNAMIC BACKTRACKING;243
7.20.7;6 ARBITRARY MOVEMENT;245
7.20.8;7 EXPERIMENTAL RESULTS;247
7.20.9;8 CONCLUSION AND FUTURE WORK;248
7.20.10;A PROOFS;248
7.20.11;References;249
7.21;Chapter 21. Representing Uncertainty in Simple Planners;251
7.21.1;Abstract;251
7.21.2;1 INTRODUCTION;251
7.21.3;2 PRELIMINARY DEFINITIONS;252
7.21.4;3 THE SIMPLE PLANNING PROBLEM;252
7.21.5;4 REGRESSION;252
7.21.6;5 ACTIONS WITH UNCERTAIN OUTCOMES;253
7.21.7;6 CNLP AND PLINTH;254
7.21.8;7 UNCERTAINTY AND SECONDARY PRECONDITIONS;255
7.21.9;8 CASSANDRA;256
7.21.10;9 INFORMATION-GATHERING ACTIONS;256
7.21.11;10 OTHER RELATED WORK;257
7.21.12;11 POSSIBLE EXTENSIONS;257
7.21.13;12 SUMMARY AND CONCLUSIONS;257
7.21.14;References;258
7.22;Chapter 22. How Far Can We 'C' ? Defining a 'Doughnut' Using Connection Alone;259
7.22.1;Abstract;259
7.22.2;1 INTRODUCTION;259
7.22.3;2 CLARKE'S LOGIC OF CONNECTION, AND RCC'S VERSION;261
7.22.4;3 DEFINING A DOUGHNUT MADE EASY;262
7.22.5;4 DEFINING A DOUGHNUT MADE LESS EASY;264
7.22.6;5 DEFINING A DOUGHNUT MADE HARDER STILL;267
7.22.7;6 Discussion: HOW FAR CAN C TAKE US?;268
7.22.8;Acknowledgements;269
7.22.9;References;270
7.23;Chapter 23. An Ontology for Engineering Mathematics;271
7.23.1;Abstract;271
7.23.2;1. INTRODUCTION;271
7.23.3;2. THE PURPOSE OF THE ONTOLOGY;271
7.23.4;3. OVERVIEW OF THE CONCEPTUALIZATION;273
7.23.5;4. RATIONALE FOR IMPORTANT DISTINCTIONS;277
7.23.6;5. DESIGN AND EVALUATION ISSUES;279
7.23.7;6. RELATED WORK;280
7.23.8;Acknowledgments;281
7.23.9;References;281
7.24;Chapter 24. An Ontology of Meta-Level Categories;283
7.24.1;Abstract;283
7.24.2;1 INTRODUCTION;283
7.24.3;2 REDS AND APPLES;285
7.24.4;3 THE FORMAL FRAMEWORK;285
7.24.5;4 A BASIC ONTOLOGY OF UNARY PREDICATE TYPES;287
7.24.6;5 ONTOLOGICAL ENGINEERING;290
7.24.7;6 CONCLUSIONS;291
7.24.8;Acknowledgements;292
7.24.9;References;292
7.25;Chapter 25. Defeasible reasoning with structured information;294
7.25.1;Abstract;294
7.25.2;1 INTRODUCTION;294
7.25.3;2 STRUCTURED INFORMATION;295
7.25.4;3 NAIVE INFERENCES;295
7.25.5;4 PREFERRED INFERENCES;296
7.25.6;5 INFLUENCE RELATIONS;296
7.25.7;6 STRONGFORWARD LOGICS;297
7.25.8;7 FRAMEWORK EXAMPLES;300
7.25.9;8 FRAMEWORK ISSUES;302
7.25.10;9 AGGREGATION PRINCIPLES;303
7.25.11;10 DISCUSSION;303
7.25.12;Acknowledgements;304
7.25.13;References;304
7.26;Chapter 26. On Positive Occurrences of Negation as Failure;306
7.26.1;Abstract;306
7.26.2;1 Introduction;306
7.26.3;2 Answer Sets of Programs with Positive Occurrences of not;307
7.26.4;3 Representing Abduction by GEDP;308
7.26.5;4 Complexity and Computation;310
7.26.6;5 Relation to Autoepistemic Logic;313
7.26.7;6 Discussion;315
7.26.8;7 Conclusion;316
7.26.9;Acknowledgements;316
7.26.10;References;316
7.27;Chapter 27. Probabilistic Reasoning in Terminological Logics;318
7.27.1;Abstract;318
7.27.2;1 INTRODUCTION;318
7.27.3;2 SYNTAX;319
7.27.4;3 SEMANTICS;320
7.27.5;4 COMPUTING PROBABILITIES;323
7.27.6;5 A PROBABILISTIC VERSION OF ACC;326
7.27.7;6 CONCLUDING REMARKS;328
7.27.8;References;329
7.28;Chapter 28. On Multiagent Autoepistemic Logic - an extrospective view;330
7.28.1;Abstract;330
7.28.2;1 Introduction;330
7.28.3;2 Autoepistemic Logic;332
7.28.4;3 A simple multiagent autoepistemic logic AEEpis;334
7.28.5;4 Conjecture;335
7.28.6;5 Another Multiagent Autoepistemic Logic;336
7.28.7;6 MAE = AEEpis;337
7.28.8;7 Subsumption of Morgenstern's formulation;339
7.28.9;8 Conclusion;340
7.28.10;Acknowledgements;341
7.28.11;References;341
7.29;Chapter 29. Refinement Search as a Unifying Framework for analyzing Planning Algorithms;342
7.29.1;Abstract;342
7.29.2;1 Introduction;342
7.29.3;2 Refinement search Preliminaries;343
7.29.4;3 Planning as Refinement Search;344
7.29.5;4 A generalized algorithm for Refinement Planning;346
7.29.6;5 Applications of the Unified Framework;350
7.29.7;6 Extending the framework;352
7.29.8;7 Conclusion;353
7.29.9;References;353
7.30;Chapter 30. Actions with Indirect Effects (Preliminary Report);354
7.30.1;Abstract;354
7.30.2;1 Introduction;354
7.30.3;2 Syntax of ARo;355
7.30.4;3 Examples;356
7.30.5;4 Semantics of ARo;357
7.30.6;5 Two Theorems about Domain Descriptions;358
7.30.7;6 Relation to A;359
7.30.8;7 Translating from ARo into Circumscription;359
7.30.9;8 Conclusion;362
7.30.10;Acknowledgements;362
7.30.11;References;363
7.31;Chapter 31. An Application of Terminological Logics to Case-based Reasoning;364
7.31.1;Abstract;364
7.31.2;1 INTRODUCTION;364
7.31.3;2 THE SOLUTION;365
7.31.4;3 AN EXAMPLE;367
7.31.5;4 IMPLEMENTATION;373
7.31.6;5 RELATED WORK;374
7.31.7;6 CONCLUSION;374
7.31.8;Acknowledgements;374
7.31.9;References;374
7.32;Chapter 32. Risk-Sensitive Planning with Probabilistic Decision Graphs;376
7.32.1;Abstract;376
7.32.2;1 Introduction;376
7.32.3;2 The Planning Framework;377
7.32.4;3 The Problem;378
7.32.5;4 A Solution;380
7.32.6;5 Conclusion;385
7.32.7;Acknowledgements;385
7.32.8;References;385
7.33;Chapter 33. Easy to be Hard: Difficult Problems for Greedy Algorithms;387
7.33.1;Abstract;387
7.33.2;1 Introduction;387
7.33.3;2 Graph crosswords;388
7.33.4;3 The experiments;388
7.33.5;4 Analysis;389
7.33.6;5 Conclusion;391
7.33.7;References;391
7.34;Chapter 34. Complexity Results for First-Order Theories of Temporal Constraints;392
7.34.1;Abstract;392
7.34.2;1 INTRODUCTION;392
7.34.3;2 FIRST-ORDER THEORIES OF POINT CONSTRAINTS;393
7.34.4;3 NAIVE QUANTIFIER ELIMINATION ALGORITHMS;393
7.34.5;4 AN IMPROVED QUANTIFIER ELIMINATION ALGORITHM FOR diPC;394
7.34.6;5 AN IMPROVED QUANTIFIER ELIMINATION ALGORITHM FOR dePC;398
7.34.7;6 THEORIES OF POINT AND INTERVAL CONSTRAINTS;400
7.34.8;7 CONCLUSIONS;401
7.34.9;Acknowledgements;401
7.34.10;References;402
7.35;Chapter 35. Reasoning in Logic about Continuous Systems;404
7.35.1;Abstract;404
7.35.2;1 INTRODUCTION;404
7.35.3;2 BTL AND EBTL;405
7.35.4;3 QSIM AND THE IMPLEMENTATION OF THE LOGIC;407
7.35.5;4 THE MAIN THEOREM;412
7.35.6;5 APPLICATIONS OF EBTL AND QSIM;413
7.35.7;6 FUTURE DIRECTIONS;414
7.35.8;7 MISCELLANY;414
7.35.9;8 CONCLUSION;415
7.35.10;Acknowledgements;415
7.35.11;References;415
7.36;Chapter 36. Enhancing the Power of a Decidable First-Order Reasoner;416
7.36.1;Abstract;416
7.36.2;1 Introduction;416
7.36.3;2 The Logic BLqs;417
7.36.4;3 On Decidable Belief Implication in BLqs;421
7.36.5;4 Sorted Introspective Reasoning;424
7.36.6;5 Conclusion;426
7.36.7;Acknowledgements;426
7.36.8;References;426
7.37;Chapter 37. Knowledge, Certainty, Belief, and Conditionalisation (abbreviated version);428
7.37.1;Abstract;428
7.37.2;1 Introduction;428
7.37.3;2 Belief, certainty, and knowledge: the language;430
7.37.4;3 Belief, certainty, and knowledge: a model theory;430
7.37.5;4 Belief, certainty, and knowledge: an axiomatic system;432
7.37.6;5 Related work;434
7.37.7;6 Conclusions;436
7.37.8;Acknowledgements;436
7.37.9;References;436
7.38;Chapter 38. How to Progress a Database (and Why) I. Logical Foundations;438
7.38.1;Abstract;438
7.38.2;1 INTRODUCTION;438
7.38.3;2 LOGICAL PRELIMINARIES;439
7.38.4;3 BASIC ACTION THEORIES;439
7.38.5;4 FORMAL FOUNDATIONS;441
7.38.6;5 PROGRESSION WITH RELATIVELY COMPLETE INITIAL DATABASES;445
7.38.7;6 PROGRESSION IN THE CONTEXT FREE CASE;446
7.38.8;7 SUMMARY;448
7.38.9;Acknowledgements;449
7.38.10;References;449
7.39;Chapter 39. Modalities Over Actions, I. Model Theory;450
7.39.1;Abstract;450
7.39.2;1 Introduction;450
7.39.3;2 Intuitions and Applications;451
7.39.4;3 Events and Actions;454
7.39.5;4 Deontic Modalities;457
7.39.6;5 Discussion;460
7.39.7;References;460
7.40;Chapter 40. Generating Tests using Abduction;462
7.40.1;Abstract;462
7.40.2;1 INTRODUCTION;462
7.40.3;2 PRELIMINARIES;463
7.40.4;3 TEST GENERATION AS ABDUCTION;465
7.40.5;4 PRACTICAL BENEFITS;467
7.40.6;5 SUMMARY;472
7.40.7;Acknowledgements;472
7.40.8;References;472
7.41;Chapter 41. Preferential entailments for circumscriptions;474
7.41.1;Abstract;474
7.41.2;1 Introduction;474
7.41.3;2 Preferential entailment;474
7.41.4;3 Circumscriptions;476
7.41.5;4 General properties;477
7.41.6;5 Some circumscriptions viewed as preferential entailment;479
7.41.7;6 Conclusion;484
7.41.8;Acknowledgements;484
7.41.9;References;484
7.42;Chapter 42. A Decision Method for Nonmonotonic Reasoning Based on Autoepistemic Reasoning;486
7.42.1;Abstract;486
7.42.2;1 INTRODUCTION;486
7.42.3;2 AUTOEPISTEMIC LOGIC;487
7.42.4;3 OTHER FORMS OF NONMONOTONIC REASONING;489
7.42.5;4 AUTOMATING NONMONOTONIC REASONING;489
7.42.6;5 CONCLUSIONS;496
7.42.7;References;497
7.43;Chapter 43. A Framework for Part-of Hierarchies in Terminological Logics;498
7.43.1;Abstract;498
7.43.2;1 INTRODUCTION;498
7.43.3;2 LANGUAGE;499
7.43.4;3 KEY RELATIONS;501
7.43.5;4 COMPOSITIONAL EXTENSIONS;502
7.43.6;5 DISCUSSION AND CONCLUSIONS;508
7.43.7;Acknowledgements;509
7.43.8;References;509
7.44;Chapter 44. Means-End Plan Recognition - Towards a Theory of Reactive Recognition;510
7.44.1;Abstract;510
7.44.2;1 INTRODUCTION;510
7.44.3;2 MEANS-END PLAN EXECUTION AND RECOGNITION;511
7.44.4;3 ALGORITHMS;512
7.44.5;4 DYNAMIC AGENT LOGIC;514
7.44.6;5 REACTIVE RECOGNITION;519
7.44.7;6 COMPARISON AND CONCLUSIONS;520
7.44.8;Acknowledgements;520
7.44.9;References;521
7.45;Chapter 45. Terminological Cycles and the Propositional µ-Calculus;522
7.45.1;Abstract;522
7.45.2;1 Introduction;522
7.45.3;2 The Terminological Logic ACC;524
7.45.4;3 Syntactically Monotone Fixpoint Terminologies;525
7.45.5;4 The Terminological Logic ACCµ;528
7.45.6;5 Expressive Power;530
7.45.7;6 Computational Complexity;531
7.45.8;7 Conclusion;532
7.45.9;Acknowledgements;533
7.45.10;References;533
7.46;Chapter 46. Near-Optimal Plans, Tractability, and Reactivity;534
7.46.1;Abstract;534
7.46.2;1 INTRODUCTION;534
7.46.3;2 DOMAIN-INDEPENDENT PLANNING;535
7.46.4;3 DOMAIN-DEPENDENT PLANNING;536
7.46.5;4 TRACTABILITY: REACTIVE PLANNING AND UNIVERSAL PLANS;538
7.46.6;5 CONCLUSIONS;540
7.46.7;Acknowledgments;541
7.46.8;References;541
7.46.9;Appendix;541
7.47;Chapter 47. Specification and Evaluation of Preferences under Uncertainty;543
7.47.1;Abstract;543
7.47.2;1 Introduction;543
7.47.3;2 Preference Specification;544
7.47.4;3 Evaluation of Preferences;547
7.47.5;4 Quantified Conditional Desires;548
7.47.6;5 Comparison with Related Work;550
7.47.7;6 Conclusion;550
7.47.8;Acknowledgements;552
7.47.9;References;552
7.48;Chapter 48. Making the Difference: A Subtraction Operation for Description Logics;553
7.48.1;Abstract;553
7.48.2;1 INTRODUCTION;553
7.48.3;2 THE DIFFERENCE OPERATION IN DESCRIPTION LOGICS;553
7.48.4;3 THE DIFFERENCE OPERATION IN SPECIFIC DESCRIPTION LOGICS;556
7.48.5;4 APPLICATIONS;561
7.48.6;5 CONCLUSION;562
7.48.7;Acknowledgments;562
7.48.8;References;563
7.49;Chapter 49. Tractable Databases: How to Make Propositional Unit Resolution Complete through Compilation;564
7.49.1;Abstract;564
7.49.2;1 INTRODUCTION;564
7.49.3;2 NO-MERGE RESOLUTION AND ITS RELATION TO UNIT RESOLUTION;565
7.49.4;3 COMPILATION;566
7.49.5;4 TIED CHAINS, MERGES, AND ORDERING STRATEGIES;570
7.49.6;5 A COMPLETE LTMS;572
7.49.7;6 EXPERIMENTAL RESULTS;573
7.49.8;7 DISCUSSION;573
7.49.9;Acknowledgements;574
7.49.10;References;574
7.50;Chapter 50. The Role of Reversible Grammars in Translating Between Representation Languages;575
7.50.1;Abstract;575
7.50.2;1 Introduction;575
7.50.3;2 Interlingua-Based Translations and Semantics;576
7.50.4;3 Definite Clause Translation Grammars;577
7.50.5;4 Reversible Definite Clause Translation Grammars;581
7.50.6;5 Showing that a Translator is Reversible;582
7.50.7;6 Ongoing Work;583
7.50.8;7 Summary;583
7.50.9;Acknowledgments;584
7.50.10;References;584
7.51;Chapter 51. Constraint Tightness versus Global Consistency;585
7.51.1;Abstract;585
7.51.2;1 Introduction;585
7.51.3;2 Background;586
7.51.4;3 Binary constraint networks;587
7.51.5;4 R-ary constraint networks;589
7.51.6;5 Conclusions;594
7.51.7;Acknowledgements;595
7.51.8;References;595
7.52;Chapter 52. Honesty in Partial Logic;596
7.52.1;Abstract;596
7.52.2;1 INTRODUCTION;596
7.52.3;2 THE LOGIC;598
7.52.4;3 HONESTY;601
7.52.5;4 CONCLUSION;606
7.52.6;Acknowledgements;607
7.52.7;References;607
7.53;Chapter 53. Mutual Belief Revision (Preliminary Report);608
7.53.1;Abstract;608
7.53.2;1 INTRODUCTION;608
7.53.3;2 PRELIMINARIES;609
7.53.4;3 A Theory of Mutual Belief Revision;612
7.53.5;4 Scientists in Conference;614
7.53.6;5 Speech Act Semantics;616
7.53.7;6 Conclusion;618
7.53.8;Acknowledgements;618
7.53.9;References;619
7.54;Chapter 54. REVISE: An Extended Logic Programming System for Revising Knowledge Bases;620
7.54.1;Abstract;620
7.54.2;1 INTRODUCTION;620
7.54.3;2 REVIEW OF THE LOGIC PROGRAMMING BASIS;620
7.54.4;3 PREFERENCE LANGUAGE AND SEMANTICS;622
7.54.5;4 EXAMPLES OF APPLICATION;623
7.54.6;5 REVISION ALGORITHM;627
7.54.7;6 COMPARISONS AND CONCLUSIONS;630
7.54.8;Acknowledgements;631
7.54.9;References;631
7.55;Chapter 55. Transmutations of Knowledge Systems;632
7.55.1;Abstract;632
7.55.2;1 INTRODUCTION;632
7.55.3;2 THE AGM PARADIGM;633
7.55.4;3 ORDINAL CONDITIONAL FUNCTIONS;634
7.55.5;4 ORDINAL EPISTEMIC ENTRENCHMENT FUNCTIONS;637
7.55.6;5 TRANSLATIONS;639
7.55.7;6 RELATED WORK;640
7.55.8;7 DISCUSSION;640
7.55.9;Acknowledgements;641
7.55.10;References;641
8;Part II: InvitedTalks;644
8.1;Chapter 56. Knowledge Representation Issues in Integrated Planning and Learning Systems;646
8.1.1;Abstract;646
8.2;Chapter 57. Non-Standard Theories of Uncertainty in Knowledge Representation and Reasoning;647
8.2.1;INTRODUCTION;647
8.2.2;1 PLAUSIBLE EXCEPTION-TOLERANT INFERENCE;647
8.2.3;2 LIMITATIONS OF CLASSICAL LOGIC;648
8.2.4;3 LIMITATIONS OF BAYESIAN NETWORKS;648
8.2.5;4 LESSONS FROM BAYESIAN NETWORKS;650
8.2.6;5 GRADED REPRESENTATIONS OF INCOMPLETE KNOWLEDGE;651
8.2.7;6 POSSIBILISTIC LOGIC;654
8.2.8;7 PROPERTIES OF EXCEPTION-TOLERANT INFERENCE;655
8.2.9;8 POSSIBILISTIC ENCODING OF RATIONAL INFERENCE;656
8.2.10;CONCLUSION;657
8.2.11;References;657
8.3;Chapter 58. Beyond Ignorance-Based Systems;659
8.3.1;Abstract;659
9;Part III: Panels;660
9.1;Chapter 59. Systems vs. Theory vs....: KR&R Research Methodologies;662
9.1.1;Abstract;662
9.2;Chapter 60. Exploiting Natural Language for Knowledge Representation and Reasoning;663
9.2.1;Abstract;663
10;Contributions by Topic;666
11;Author Index;668