Front Cover	1
	Readings in Qualitative Reasoning About Physical Systems	4
	Copyright Page	5
	Table of Contents	8
	Preface	6
	Qualitative Physics: A Personal View	14
	1. The Confusion Seminar	15
	2. Qualitative Reasoning for Solving Physics Problems	15
	3. Qualitative and Causal Reasoning for Circuit Diagnosis	17
	4. Qualitative and Causal Reasoning for Design	18
	5. Causality, Structure, and Function	19
	6. Are We Doing Physics or Psychology?	20
	7· Whither Qualitative Physics?	20
	Part 1: Overview and Motivation	22
	Introduction	22
	Chapter 1. Qualitative Physics: Past, Present, and Future	24
	1 Introduction	24
	2 Why Qualitative Physics	24
	3 The Past	27
	4 The State of the Art	30
	5 The Frontier	45
	Acknowledgments	49
	References	49
	Chapter 1.2 Multiple Representations of Knowledge in a Mechanics Problem-Solver	53
	Abstract	53
	Introduction	53
	Theory	53
	The Program NEWTON	54
	Envisioning and Planning	56
	Problem Formulation	57
	Concluding Remarks	57
	Acknowledgements	58
	References	58
	Chapter 1.3 The Second Naive Physics Manifesto	59
	1. Preface	59
	2. Introduction	59
	3. What the Proposal Isn't	59
	4. Theories, Tokens and Closure	61
	5. Meanings, Theories and Model Theory	63
	6. Discovering Intuitions and Building Theories	65
	7. Clusters	67
	8. Getting It Done	73
	9. Why It Needs To Be Done	75
	10. Is This Science?	76
	Acknowledgments	76
	Reference	76
	Chapter 1.4 Modeling Simultaneous Actions and Continuous Processes	77
	1. Introduction: World Modeling	77
	2. Realizing the Philosophy of Processes	77
	3. World Modeling in Conventional Robot Systems	78
	4. A Qoser Look at the Nature of Processes	79
	5. The Process Model: An Overview	80
	6. A Sample World	82
	7. Elementary Examples of Scenarios	82
	8. More Complex Scenarios: The Filling of a Bucket	84
	9. Scenarios with Effects Sandwiches	86
	10. Scenarios for Conventional Robot Operati	88
	11. Modeling the Execution of Plans	91
	12. Implementation	93
	13. Summary	93
	ACKNOWLEDGMENTS	94
	REFERENCES	94
	Chapter 2. Qualitative Simulation	96
	Introduction	96
	2.1 A Qualitative Physics Based on Confluences	101
	1. Introduction	101
	2. Naive Physics	104
	3. Modeling Structure	107
	4. Prediction of Behavior	114
	5. Explanation of Behavior	122
	6. Causality and Digital Physics	126
	7. Summary	135
	Appendix A. Interpretations	136
	Appendix B. A Procedure for Constructing the Expanded Episode Diagram	138
	ACKNOWLEDGMENT	138
	REFERENCES	138
	Chapter 2.2 Qualitative Reasoning with Higher-Order Derivatives	140
	ABSTRACT	140
	INTRODUCTION	140
	QUALITATIVE MODELING	140
	SIMULATION	141
	RULE(O) : VALUE CONTINUITY	141
	RULE(1): CONTRADICTION AVOIDANCE	142
	QUALITATIVE AMBIGUITY	142
	RULE(2): INSTANT CHANGK RULE	143
	RULE(3): DERIVATIVE CONTINUITY	143
	RULE(4) : DERIVA UVE INSTANT CHANGE RULE	143
	INSTANTS	143
	RULE (5): HIGHER-ORDER DERIVATIVES	144
	RULE(6): NO CHANGE TO ALL ZERO DERIVATIVES	144
	QUALITATIVE vs. QUANTITATIVE	144
	OPEN PROBLEMS	145
	ACKNOWLEDGMENTS	145
	REFERENCES	145
	Chapter 2.3 Temporal Qualitative Analysis: Explaining How Physical Systems Work	146
	Abstract	146
	1. Introduction	146
	2. Qualitative Values	150
	3. Causal Propagation	152
	4. Transition Analysis	157
	5. Feedback Analysis	164
	6. Complex Qualitative Values and Operating Regions	177
	7. Discussion	184
	8. Appendix: Transition Ordering Rules	188
	References	189
	Chapter 2.4 Qualitative Process Theory	191
	1. Introduction	191
	2. Objects and Quantities	195
	3. Processes	200
	4. Examples	209
	5. Further Consequences	223
	6. Discussion	229
	ACKNOWLEDGMENT	231
	REFERENCES	231
	Chapter 2.5 The Qualitative Process Engine	233
	1. Introduction	233
	2. Using an ATMS	234
	3. The Qualitative Process Engine	238
	4. Conclusions	246
	5. Acknowledgements	247
	References	247
	Chapter 2.6 Qualitative Simulation	249
	1. Introduction	249
	2. Qualitative Behavior	253
	3. Qualitative Structure	255
	4. Qualitative Simulation	257
	5. Questions and Answers	261
	Appendix A. The Qualitative State Transitions	265
	Appendix B. Constraint Consistency	268
	Appendix C. The QSIM Program and its Output	272
	ACKNOWLEDGMENT	272
	REFERENCES	273
	Chapter 2.7 Taming Intractable Branching in Qualitative Simulation	274
	Abstract	274
	1. Introduction	274
	2. Ignoring Irrelevant Distinctions	276
	3. Applying Higher-Order Derivatives	277
	4. Conclusions	279
	5. References	280
	Chapter 2.8 Non-intersection of Trajectories in Qualitative Phase Space: A Global Constraint for Qualitative Simulation	281
	Abstract	281
	1. Introduction	281
	2. The Phase Space View	281
	3. The Non-IntersectionConstraint	282
	4. Implementation	283
	5. An Example	283
	6. Discussion	284
	7. Related Work	284
	8. Conclusions	285
	Acknowledgments	285
	References	285
	Chapter 2.9 Global Filters for Qualitative Behaviors	286
	Abstract	286
	1. Introduction	286
	2. Outline of the Paper	286
	3. Some Questions	286
	4. Infering Qualitative Behavior	286
	5. Filtering Behaviors	287
	6. Exploiting the Phase Portrait	288
	7. Summary	290
	Acknowledgements	290
	References	290
	Chapter 2.10 Reasoning about Discontinuous Change	291
	ABSTRACT	291
	I. Introduction	291
	II. Properties of Discontinuous Change	291
	?II. Previous Work	292
	IV. The Approximation Method	293
	V. The Direct Method	294
	VI. Comparison and Concluding Remarks	296
	References	296
	Chapter 3. Mathematical Aspects of Qualitative Reasoning	298
	Introduction	298
	3.1 Problems of Interval-Based Qualitative Reasoning	301
	Abstract	301
	1. Introduction	301
	2. A Framework for Analyzing Qualitative Reasoning Methods	302
	3. Qualitative Reasoning Methods for Equations	305
	4. Interval Arithmetic 1	306
	5. A Modified Concept of Solution -Interval Arithmetic 2	309
	6. Arithmetic on a Finite Number ofIntervals - Interval Arithmetic 3	315
	7. Summary	317
	Acknowledgements	317
	References	318
	Chapter 3.2 Assembling a Device	319
	Abstract	319
	1. Introduction	319
	2. Assembling some devices	319
	3. Scanning the qualitative resolution rule	321
	4. Completeness of qualitative resolution	323
	5. Task-oriented confluences	324
	6. Conclusion	324
	References	324
	Chapter 3.3 MINIMA A Symbolic Approach to Qualitative Algebraic Reasoning	325
	Abstract	325
	1. Introduction	325
	2. Example: Culinary Design	325
	3. The Qualitative Algebra Q1	326
	4. Properties of Q1	327
	5. Using a Qualitative Algebra for Design	328
	6. MINIMA	329
	7. Example Revisited	330
	8. Discussion	330
	References	330
	Chapter 3.4 Order of Magnitude Reasoning	331
	ABSTRACT	331
	INTRODUCTION	331
	I. A SIMPLE EXAMPLE	331
	II. FOG	332
	III. BACK TO THE EXAMPLE	333
	IV. VALIDITY OF FOG IN NON-STANDARD ANALYSIS	334
	V. HOW TO USE FOG	334
	VI. FOG AND THE QUANTITY SPACE	335
	CONCLUSION	335
	ACKNOWLEDGMENTS	335
	REFERENCES	335
	Chapter 3.5 Formal Order-of-Magnitude Reasoning in Process Engineering	336
	1. INTRODUCTION	336
	2. PREVIOUS WORK	337
	3. THE SCOPE OF ORDER-OF-MAGNITUDE REASONING IN PROCESS ENGINEERING	338
	4. THE O(M) FORMALISM	339
	5. IMPLEMENTATION	344
	6. DETAILED REASONING EXAMPLES	345
	7. DISCUSSION	348
	8. CONCLUSIONS	348
	REFERENCES	348
	Chapter 3.6 "Commonsense" Arithmetic Reasoning	350
	Abstract	350
	1. Introduction	350
	2. The Quantity Lattice	350
	3. Results	354
	4. Relation to Other Work	355
	5. Conclusions	356
	References	356
	Chapter 3.7 Hierarchical Reasoning about Inequalities	357
	Abstract	357
	I. Introduction	357
	II. The Context Manager	358
	III· Bounding Algorithms	358
	IV. Related Work	360
	V. Conclusions	361
	References	362
	Chapter 4. History-Based Simulation and Temporal Reasoning	364
	Introduction	364
	4.1 Doing Time: Putting Qualitative Reasoning on Firmer Ground	366
	Abstract	366
	1. Introduction	366
	2. Qualitative Reasoning In A Nutshell	366
	3. Limitations of the Existing Approach	367
	4. Representing Behavior Over Time	367
	5. Propagation of Constraints	368
	6. The Basic Constraint Propagator	368
	7. Temporal Constraint Propagatior	368
	8. Histories	368
	9. Making Histories Concise	369
	10. The Time Box	370
	11. Modeling Time for Feedback Systems	371
	12. Qualitative Reasoning Revisited	372
	13. Summary and Research Status	373
	14. Acknowledgements	373
	References	373
	Chapter 4.2 Maintaining Knowledge about Temporal Intervals	374
	1. INTRODUCTION	374
	2. BACKGROUND	375
	3. TIME POINTS VS. TIME INTERVALS	376
	4. MAINTAINING TEMPORAL RELATIONS	376
	5. CONTROLLING PROPAGATION: REFERENCE INTERVALS	380
	6. DISCUSSION	383
	7. FUTURE RESEARCH AND EXTENSIONS	383
	8. SUMMARY	385
	REFERENCES	385
	Chapter 4.3 Constraint Propagation Algorithms for Temporal Reasoning: A Revised Report	386
	The Interval Algebra	386
	Determining Closure in the Interval Algebra	387
	Intractability of the Interval Algebra	389
	Consequences of Intractability	390
	Restricting the Interval Algebra	390
	Time Point Algebras	391
	Continuous Endpoint Uncertainty	391
	Additional Results	393
	Applying Temporal Representations	394
	Acknowledgements	394
	References	394
	Chapter 4.4 Reasoning about Partially Ordered Events	395
	1. Introduction	395
	2. Temporal Projection	395
	3. Incomplete Decision Procedures	397
	4. Probabilistic Decision Procedures	404
	5. Conclusions	404
	Appendix A	405
	Chapter 5. Other Styles of Reasoning	408
	Introduction	408
	Chapter 5.1 Comparative Analysis	410
	1. Introduction	410
	2. Preliminaries	413
	3. Differential Qualitative Analysis	416
	4. Changes in Behavioral Topology	423
	5. Related Work	427
	6. Future Directions	428
	Appendix A. A Useful Example	428
	ACKNOWLEDGMENT	429
	REFERENCES	429
	Chapter 5.2 Exaggeration	430
	Abstract	430
	1. Introduction	430
	2. Transform Phase	431
	3. Simulate Phase	431
	4. Scale Phase	433
	5. Related Work	433
	References	434
	Chapter 5.3 Order of Magnitude Reasoning in Qualitative Differential Equations	435
	1. Introduction	435
	2. Theory	436
	3. Sample Inferences	440
	4. Algorithm	442
	5. The CHEPACHET Program	445
	6. Further Work	446
	7. References	446
	Chapter 5.4 Troubleshooting: When Modeling Is the Trouble	448
	I. Introduction	448
	II. Complexity of Troubleshooting in Analog Circuits	448
	III. Exploiting Significant Changes in Behavior	449
	IV. Qualitative Modeling in DEDALE	449
	V. Example of Diagnosis	451
	VI. Strategy	452
	VII. Conclusion	453
	Acknowledgments	453
	Appendix	453
	References	453
	Chapter 5.5 Interpreting Observations of Physical Systems	454
	I. INTRODUCTION	454
	II. INPUT DATA AND SEGMENTATION	455
	III. INTERPRETING SEGMENTS	458
	IV. CONSTRUCTING GLOBAL INTERPRETATIONS	461
	ACKNOWLEDGMENT	463
	REFERENCES	463
	Chapter 6. Automating Quantitative Analysis	464
	Introduction	464
	Chapter 6.1 Intelligence in Scientific Computing	466
	NUMERICAL MODELING CAN BE AUTOMATED	467
	INTELLIGENT NUMERICAL COMPUTING RESTS ON AI TECHNOLOGY	474
	INTELLIGENT TOOLS ARE FEASIBLE	479
	REFERENCES	481
	Chapter 6.2 Generating Global Behaviors Using Deep Knowledge of Local Dynamics	483
	Abstract	483
	1. Introduction	483
	2. Ontology	484
	3. The Task	485
	4. Characteristics of Task Domain	485
	5. Implementation	486
	6. Experiments	487
	7. Evaluating the performance	487
	8. Conclusion	488
	References	488
	Chapter 6.3 Piecewise Linear Reasoning	489
	Abstract	489
	I. Introduction	489
	II. The PLR Methodology	489
	III. The Lienard Equation	490
	IV. The Van der Pol Equation	491
	V. Previous Work	492
	VI. Implementation Status	493
	VII. Conclusions	493
	References	493
	Chapter 7. Multiple Ontologies and Automated Modeling	494
	Introduction	494
	Chapter 7.1 Naive Physics I: Ontology for Liquids	497
	1. Introduction	497
	2. Individuals and Individuation	497
	3. The Problem With Liquids	498
	4. Doing Without Liquid Individuals: Containment	499
	5. Space: Places, Enclosures and Portals	500
	6. The Fifteen States of Liquids	504
	7. Change and Movement: Histories	506
	8. Histories of Lazy Bulk Liquid	508
	9. Some Examples	511
	10. Liquid Individuals Revisited	513
	11. Further Works	514
	Acknowledgments	515
	References	515
	Chapter 7.2 Reasoning about Fluids via Molecular Collections	516
	Abstract	516
	I. Introduction	516
	II. The theory of molecular collections	516
	III. Examples	518
	IV. Discussion	519
	V. Acknowledgements	520
	References	520
	Chapter 7.3 Multiple Models of Evaporation Processes	521
	Aggregate ?odels	523
	A Molecular Model	524
	Conclusion	525
	References	525
	Chapter 7.4 The Use of Aggregation in Causal Simulation	526
	1. Introduction	526
	2. Demonstration	528
	3. Representing State and Change	530
	4. Aggregation	532
	5. Applicability	539
	6. Related Work	541
	7. Conclusion	542
	ACKNOWLEDGMENT	542
	REFERENCES	542
	Chapter 7.5 Abstraction by Time-Scale in Qualitative Simulation	543
	1. The Problem of Scale	543
	2. Time-Scale Abstraction	543
	3. Communicating Across Time-Scales	545
	4. Conclusions	547
	5. References	547
	Chapter 7.6 Diagnosis via Causal Reasoning: Paths of Interaction and the Locality Principle	548
	Abstract	548
	1. INTRODUCTION	548
	2. CENTRAL CONCERNS	548
	3. BACKGROUND	548
	4. LAYERS OF INTERACTION EXAMPLE: DIAGNOSING A BRIDGE FAULT	550
	5. PATHS OF INTERACTION	553
	6. SUMMARY	554
	REFERENCES	554
	Chapter 7.7 Granularity	555
	Abstract	555
	Abstraction	555
	Simplification	555
	Idealization	556
	Articulation	557
	Intelligence	558
	Acknowledgments	558
	References	558
	Chapter 7.8 Reasoning About Assumptions in Graphs of Models	559
	Abstract	559
	1. Introduction	559
	2. Graphs of Models	560
	3. Conflicts	561
	4. Delta-Vectors	561
	5. Assumption Knowledge	562
	6. Selecting a Better Model	563
	7. Conclusions and Future Work	564
	References	565
	Chapter 7.9 Setting Up Large-Scale Qualitative Models	566
	Abstract	566
	1. Introduction	566
	2. The Modeling Process	566
	3. A steam plant model	567
	4. Modeling Assumptions	567
	5. Organization of the model	569
	6. Model selection for question-answering	570
	7. Discussion	571
	8. Acknowledgements	571
	References	571
	Chapter 8. Reasoning About Shape and Space	572
	Introduction	572
	Chapter 8.1 Qualitative Kinematics: A Framework	575
	Abstract	575
	I. Introduction	575
	II. A Framework for Qualitative Kinematics	576
	III. Example: FROB	578
	IV. The Clock system	579
	V. Other QK systems	579
	VI. Discussion	580
	VII. Acknowledgements	580
	References	580
	Chapter 8.2 Qualitative Kinematics in Mechanisms	581
	Abstract	581
	1. Introduction	581
	2. Place Vocabularies	582
	3. Descriptive Power of the Place Vocab-ulary	584
	4. Computation of Place Vocabular	584
	5. Conclusions	586
	References	586
	Chapter 8.3 Shape and Function in Mechanical Devices	588
	Abstract	588
	I. Introduction	588
	II. An algorithm for the analysis of mechanisms	589
	III. Local Interactions Analysis	589
	IV. Global Interactions Analysis	591
	V. Conclusions and future work	592
	Acknowledgments	592
	References	592
	Chapter 8.4 Automated Reasoning about Machine Geometry and Kinematics	593
	Abstract	593
	Bibliography	604
	Chapter 8.5 A Qualitative Approach to Mechanical Constraint	605
	Abstract	605
	1. Introduction	605
	2. Representations	605
	3. Mechanical Motion	606
	4. Sample Mechanism	609
	5. Discussion	609
	6. Acknowledgements	609
	References	609
	Chapter 8.6 Simplification and Abstraction of Kinematic Behaviors	610
	Abstract	610
	1. Introduction	610
	2. Describing Kinematic Behavior	611
	3. Simplification and Abstraction Operators	612
	4. Comparing Two Mechanisms	614
	5. Conclusion	615
	References	615
	Chapter 8.7 A Framework for Qualitative Reasoning about Solid Objects	616
	1. Abstract	616
	2. Introduction	616
	3. Background	616
	4. Examples and Analysis	618
	5. The Block on the Table	619
	6. The Underlying Knowledge	619
	7. Ontology	620
	8. Axioms for Physical Reasoning	620
	9. Conclusions	621
	10. Acknowledgements	622
	11. References	622
	Chapter 9. Causal Explanations of Behavior	624
	Introduction	624
	Chapter 9.1 The Declarative Representation and Procedural Simulation of Causality in Physical Mechanisms	630
	Abstract:	630
	1. Introduction	630
	2. Motivation	630
	3. Background and Related Work	630
	4. Theoretical Framework	630
	5. Simulation Strategy	632
	6. The Mechanisms Simulator	633
	7. Simulation Philosophy	634
	8. Conclusions	635
	Acknowledgments	635
	References	635
	Chapter 9.2 The Origin and Resolution of Ambiguities in Causal Arguments	637
	Abstract	637
	Introduction	637
	Theory	638
	Generating Causal Arguments	639
	Device Models for Electronics	639
	Ambiguities and Assumptions	641
	The Role of Teleology	642
	Conclusions	642
	Acknowledgements	643
	References	643
	Chapter 9.3 Causality in Device Behavior	644
	1. Introduction	644
	2. Causal Ordering	647
	3. Mythical Causality	649
	4. Comparison of the Two Concepts of Causality	651
	5. Systems with Feedback	654
	6. Conclusion	657
	Appendix A. Derived Structures of Higher Orders, for the Evaporator Model	658
	A.2. Derived structure of the second order	658
	A.3. Derived structure of the third order	658
	ACKNOWLEDGMENT	658
	REFERENCES	658
	Chapter 9.4 Theories of Causal Ordering	659
	1. Introduction	659
	2. Propagation of Constraints	661
	3. Comparison of the Differing Approaches to Causality	664
	4. Feedback in the Conduit	665
	5. Comparative Statics	667
	6. Ambiguity and Feedback	670
	7. Conclusion	671
	ACKNOWLEDGMENT	672
	REFERENCES	673
	Chapter 9.5 Theories of Causal Ordering: Reply to de Kleer and Brown	674
	1. Introduction	674
	2. Propagation of Constraints	675
	3. Comparison of the Differing Approaches to Causality	676
	4. Feedback in the Conduit	676
	5. Comparative Statics	677
	6. Ambiguity and Feedback	677
	7. Conclusion	678
	REFERENCES	678
	Chapter 9.6 Causal Reasoning about Quantities	679
	Abstract	679
	1· Introduction	679
	2. Models of causality in changing quantities	679
	3. Psychological Implications	684
	4· Conclusions	689
	5. Acknowledgements	689
	6. Bibliography	689
	Bibliography	692
	Author Index	706
	Subject Index	710
	Credits	732