Artificial Intelligence IV (eBook)

Methodology, Systems, Applications

P. Jorrand, V. Sgurev (Herausgeber)

eBook Download: PDF

2016 | 1. Auflage
450 Seiten
Elsevier Science (Verlag)
978-1-4832-9778-1 (ISBN)

Infos

Presenting recent results and ongoing research in Artificial Intelligence, this book has a strong emphasis on fundamental questions in several key areas: programming languages, automated reasoning, natural language processing and computer vision.AI is at the source of major programming language design efforts. Different approaches are described, with some of their most significant results: languages combining logic and functional styles, logic and parallel, functional and parallel, logic with constraints.A central problem in AI is automated reasoning, and formal logic is, historically, at the root of research in this domain. This book presents results in automatic deduction, non-monotonic reasoning, non-standard logic, machine learning, and common-sense reasoning. Proposals for knowledge representation and knowledge engineering are described and the neural net challenger to classical symbolic AI is also defended.Finally, AI systems must be able to interact with their environment in a natural and autonomous way. Natural language processing is an important part of this. Various results are presented in discourse planning, natural language parsing, understanding and generation. The autonomy of a machine for perception of its physical environment is also an AI problem and some research in image processing and computer vision is described.

Inhalt

Front Cover 1
Artificial Intelligence IV: Methodology, Systems, Applications 4
Copyright Page 5
Table of Contents 12
FOREWORD 6
ACKNOWLEDGEMENTS 8
CONFERENCE CHAIRMAN 10
PART: 1. AUTOMATED REASONING AND LOGICS FOR AI 18
Chapter 1. The Use of Renaming to Improve the Efficiency of Clausal Theorem Proving 20
Abstract 20
1 Introduction: renaming subformulas 20
2 Different renaming transformations 22
3 Comparison 24
4 Conclusion 29
Acknowledgements 29
References 29
Chapter 2. Compilation of Recursive Two-Literal Clauses into Unification Algorithms 30
Abstract 30
1 Introduction 30
2 Prerequisites 33
3 Generation of ATs from Recursive Two-Literal Clauses 36
4 Generation of Unification Algorithms 39
5 Summary 39
References 39
Chapter 3. An application of many-valued logic to decide propositional S5 formulae: a strategy designed for a parameterized tableaux-based Theorem Prover 40
Abstract 40
1. Introduction 40
2. Definitions and Notations 41
3. Improving the tableau procedure for the Lm-logics 42
4. The strategy: an algorithm for deciding S5 formulae 45
5. Description of a Parameterized Theorem Prover for n-valued logic and Examples 46
6. Conclusion and Future work 49
7. Bibliography 49
Chapter 4. Logics for Automated Reasoning in the Presence of Contradictions 50
Abstract 50
I INTRODUCTION 50
II PARACONSISTENT LOGICS 51
III A BASIC PARACONSISTENT LOGIC 52
IV TRANSITIVITY AND DISJUNCTIVE SYLLOGISM 53
V AN EXAMPLE OF APPLICATION 54
VI A WEAKLY PARACONSISTENT LOGIC 55
VII COMPARISON WITH REVISION AND NON-MONOTONIC LOGICS 57
VIII CONCLUSION 58
IX REFERENCES 58
Chapter 5. Logics with structured contexts 60
Abstract 60
1 Introduction 60
2 Context 60
3 Language 61
4 Extensions and Kripke semantics 61
5 Axiomatization and completeness 62
6 Automatic deduction 63
7 Special cases 63
8 Logic programming with contexts 64
9 Structured semantics for structured context 65
References 66
CHAPTER 6. A PROOF-THEORETIC ACCOUNT OF MODEL-PREFERENCE DEFAULT REASONING 68
1. INTRODUCTION 68
2. AN OVERVIEW OF SELMAN & KAUTZ'S SYSTEM D+
3. A PROOF SYSTEM FOR MODEL-PREFERENCE DEFAULT REASONING 70
4. AN EXAMPLE 74
5. CONCLUSION 77
BIBLIOGRAPHY 77
Chapter 7. Unexpected and unwanted results of circumscription 78
Abstract 78
1 Introduction 78
2 Predicate circumscriptions 79
3 Where the circumscription axiom is a finiteness axiom 81
4 Where minimizing P may allow to prove that P is the largest possible 82
5 Inconsistency of circumscription 83
6 Where circumscription gives only expected results 85
7 Conclusion 86
References 87
CHAPTER 8. A LOGIC FOR TRUTH MAINTENANCE REASONING 88
Abstract 88
1 Introduction 88
2 Motivation 89
3 Language 90
4 Inference 91
5 Some results about the inference relation 93
6 One special class of derivable formulae 95
7 Conclusion 97
References 97
Chapter 9. Querying an inconsistent database 98
1 Introduction 98
2 Hypothesis and informal presentation of our approach 100
3 The formalism 101
4 Presentation of approach 103
5 An example 104
6 Concluding remarks 107
References 107
APPENDIX 109
CHAPTER 10. AN APPROACH TO THE MODELLING OF NATURAL REASONING 110
1. INTRODUCTION 110
2. THE DETERMINANTS OF HUMAN REASONING 111
3. THE PROCESSES OF REASONING 113
4. CONCLUDING REMARKS 118
REFERENCES 118
CHAPTER 11. NUMBER GENERALIZATION IN LEARNING FROM EXAMPLES 120
1. INTRODUCTION 120
2. KNOWLEDGE REPRESENTATION 121
3. GENERALITY DEFINITION 122
4. GENERALIZATION RULES 125
5. USING EXAMPLES AND COUNTER-EXAMPLES 128
6. CONCLUSIONS 129
REFERENCES 129
PART 2: LANGUAGES AND COMPUTATIONAL STRUCTURES FOR AI 132
Chapter 12. About Redundant Inequalities Generated by Fourier's Algorithm 134
Abstract 134
1. Introduction 134
2. Preliminaries 135
3. Fourier's algorithm 135
4. A sub-system equivalent to S(En) 136
5. Characterisation of minimal formulae 139
6. Detection of minimal formulae 142
7. Conclusion 143
References 144
Chapter 13. Equations over Trees and Lists with Constraints 146
ABSTRACT 146
Introduction 146
Trees 147
Terms and Constraints 148
Assignments 149
Simple Systems 149
Splitting Constraints 150
Algorithm 152
Conclusion 155
Bibliography 155
CHAPTER 14. TWO ALGORITHMS FOR CONSTRAINT SYSTEM SOLVING IN PROPOSITIONAL CALCULUS AND THEIR IMPLEMENTATION IN CONSTRAINT PROGRAMMING LANGUAGES 156
1. Introduction 156
2. An example of logic programming with boolean constraints 157
3. Functionalities of the Prolog III boolean module 158
4. A production algorithm derived from SL-Resolution 159
5. A production algorithm derived from semantic evaluation 162
6. Conclusion 165
REFERENCES 165
Chapter 15. Rule Based Mechanisms for Constraint Checking in Logic Programs 166
1. Introduction 166
2. A method for checking constraints from the structure of a program 167
3. A method for checking constraints from the rules of a program 170
References 175
CHAPTER 16. A COMPILING APPROACH FOR EXPLOITING AND-OR-PARALLELISM IN LOGIC PROGRAMS 176
Abstract 176
Introduction 176
1- Compiling clauses into an execution graph 177
2- The merge of the streams in the graph nodes 184
Conclusion 184
References 185
CHAPTER 17. LOGICAL INFERENCE IN A NETWORK ENVIRONMENT 186
1. INTRODUCTION 186
2. NET-CLAUSE PROGRAMMING 186
3. LOGIC AND NET-CLAUSE PROGRAMMING 189
4. DEFAULT REASONING IN NET-CLAUSES 192
5. CONCLUSION 194
REFERENCES 195
CHAPTER 18. A PRACTICABLE APPROACH TO FUNCTIONAL LOGIC PROGRAMMING 196
1. INTRODUCTION 196
2. BASIC DEFINITIONS AND NOTATIONS 197
3. SYNTAX AND SEMANTICS OF F-PROLOG 198
4. SEMANTIC UNIFICATIONS 200
5. TYPES AS TYPE FUNCTIONS 203
6. CONCLUDING REMARKS 204
REFERENCES 205
Chapter 19. Combining Horn Clause Logic with Rewrite Rules 206
Abstract 206
1 Introduction 206
2 Equality transformation DP 210
3 Improving DP 213
4 Summary 215
References 215
CHAPTER 20. PARALLELISM IN BACKUS-LIKE FP-SYSTEMS: AN APPROACH BASED ON THE FP2 LANGUAGE 216
Abstract 216
1. INTRODUCTION 216
2. DESCRIBING MEANS OF FP* AS PROCESSES OF FP2 217
3. DISCUSSION 224
REFERENCES 225
CHAPTER 21. KOHONEN FEATURE MAPS: TOWARD INVARIANT CHARACTER RECOGNITION 226
1. INTRODUCTION 226
2. KOHONEN FEATURE MAPS 227
3. FEATURE MAPS FOR CHARACTER RECOGNITION 228
4. CONCLUSION AND DESCRIPTION OF FUTURE WORK 234
REFERENCES 234
CHAPTER 22. OCCAM Based Neural Network Description Language 236
1. Introduction 236
2. Neural network description language W 237
References 243
CHAPTER 23. HYBRID CONNECTIONIST RULE-BASED SYSTEMS 244
1. INTRODUCTION 244
2. A TWO-LEVEL HYBRID CONNECTIONIST RULE-BASED MODEL OF KNOWLEDGE REPRESENTSTION 245
3. FIRST EXAMPLE - BIRTH PREDICTION AND TREATMENT OF AN AGRICULTURAL INSECT 248
4. CORE - AN HYBRID CONNECTIONIST RULE - BASED ENVIRONMENT 250
5. CURRENT APPLICATIONS AND UNSOLVED PROBLEMS 250
6. CONCLUSIONS 251
REFERENCES 251
PART 3: KNOWLEDGE REPRESENTATION, KNOWLEDGE-BASED SYSTEMS 254
CHAPTER 24. AN OBJECT-ORIENTED REPRESENTATION FRAMEWORK FOR HIERARCHICAL EVIDENTIAL REASONING 256
1. INTRODUCTION 256
2. KNOWLEDGE REPRESENTATION FRAMEWORK 257
3. KNOWLEDGE ACQUISITION SUPPORT WITHIN THE OBJECT-ORIENTED FRAMEWORK 259
4. PROPAGATION OF UNCERTAINTY 260
5. COPING WITH IMPRECISE MEASUREMENTS 261
6. CONCLUDING REMARKS 264
REFERENCES 265
CHAPTER 25. A SYSTEMS-BASED FRAMEWORK FOR KNOWLEDGE REPRESENTATION 266
1. INTRODUCTION 266
2. NEW FEATURES FOR KNOWLEDGE REPRESENTATION 267
3. SYSTEMS 269
4. USING SYSTEMS FOR REPRESENTING KNOWLEDGE 272
5. CONCLUSIONS 274
REFERENCES 275
CHAPTER 26. MODELING OF MEDICAL DIAGNOSTIC KNOWLEDGE AND REASONING IN DEDEX EXPERT SYSTEM 276
1. INTRODUCTION 276
2. KNOWLEDGE REPRESENTATION SCHEME 277
3. INFERENCE MECHANISM SCHEME 279
4. CONCLUSION 279
REFERENCES 280
APPENDIX A 280
APPENDIX B 280
CHAPTER 27. ON THE USE OF DIAGRAMS 282
1. INTRODUCTION 282
2. RELEVANT STUDIES 283
3. EXPERIMENTAL STUDY 284
4. HYPOTHESES 284
5. PROCEDURE 285
6. MEASUREMENT OF DEPENDENT VARIABLES 287
7. RESULTS AND DISCUSSION 287
8. GENERAL DISCUSSION 289
REFERENCES 290
CHAPTER 28. DEVELOPING A KNOWLEDGE BASED SYSTEM 292
INTRODUCTION 292
1. THE CLONING PROBLEM 293
2. THE COGNITIVE MODEL 295
3. THE COMPUTING CHOICES 298
4. OTHER SYSTEMS AND ACTUAL SITUATION 299
CONCLUSION 301
REFERENCES 301
CHAPTER 29. DEFEASIBLE REASONING BY USING ANALOGIES 302
1. INTRODUCTION 302
2. COMMON VIEW OF THE PROPOSED DEFEASIBLE REASONING 303
3. APPLICATIONS OF THE DEFEASIBLE PROCEDURE IN KNOWLEDGE ACQUISITION SYSTEM 305
4. PERSPECTIVES 308
5. CONCLUSIONS 308
REFERENCES 308
CHAPTER 30. SOLVING PROGRAM CONFIGURATION TASK THROUGH A KNOWLEDGE BASED SYSTEM 310
1. INTRODUCTION 310
2. AN APPROACH FOR PROGRAM CONFIGURATION TASK SOLVING 311
3. KNOWLEDGE REPRESENTATION 313
4. IMPLEMENTATION 314
5. EXAMPLE 316
6. CONCLUSIONS 319
REFERENCES 319
PART 4: NATURAL LANGUAGE PROCESSING 320
CHAPTER 31. A FORMAL SEMANTICS FOR INTERNAL LOCALIZATION : AN ESSAY ON SPATIAL COMMONSENSE KNOWLEDGE 322
INTRODUCTION 322
1. THE GENERAL SYSTEM FOR THE CHARACTERIZATION OF SPATIAL ENTITIES 322
2. THE INTERNAL LOCALIZATION NOUNS (ILN) AND THEIR SEMANTICS 326
3. SOME COMPOSITION PRINCIPLES OF SPATIAL REFERENCE 328
4. SOME PERSPECTIVES FOR SPACE SEMANTICS 333
REFERENCES 334
CHAPTER 32. WHAT'S IN A 'DET' ? Steps towards Determiner-Dependent Inferencing 336
1 Natural Language Determiners - Problems, Types, and Theory 336
2 Linguistic Universale and Semantic Constraints of NL Determiners 338
3 Requirements for a determiner processing system 340
4 Processing determiners in an integrated NL system 343
5 Summary 345
6 Bibliography 345
Chapter 33. Dialogue Modeling and Response Generation in CFID@ a robust man-machine interface system 346
1. INTRODUCTION 346
2. AN OVERVIEW OF THE SYSTEM 347
3. THE DIALOGUE MODEL 348
4. GENERATION OF RESPONSES 353
5. CONCLUSIONS 356
REFERENCES 356
CHAPTER 34. ANALOGICAL REASONING AND SENTENCE PARSING 358
1. INTRODUCTION 358
2. ANALOGICAL REASONING 358
3. ANALOGICAL REASONING AND SENTENCE PARSING 361
4. CONCLUSION 365
REFERENCES 366
CHAPTER 35. SPEECH ACT THEORY AND EPISTEMIC PLANNING 368
1 Background 368
2 Rational Behaviour and AI Planning Theory 370
3 Speech Act Theory 372
4 Epistemic Planning 376
References 377
CHAPTER 36. SOME LINGUISTIC AND CONCEPTUAL ASPECTS IN THE GENERATION OF BULGARIAN NATURAL LANGUAGE TEXTS 378
ABSTRACT 378
1. INTRODUCTION 378
2. KNOWLEDGE REPRESENTATION APPROACH 379
3. THE TWO SIDES OF GENERATION 379
4. PRELIMINARY FACTORS FOR STRATEGY AND TACTICS 380
5. LOGICAL EMPHASIS AND SENTENCE SYNTAX 381
6. THE GRAMMAR AND SENTENCE PRODUCTION 384
7. SAMPLE TEXTS 385
REFERENCES 386
Chapter 37. Syntactic Processing of Unknown Words 388
Abstract 388
1 On the need for processing unknown words 389
2 Syntactic processing: A relational view 389
3 A method for processing unknown words 390
4 An example 390
5 Problems 397
6 Conclusion 398
Bibliography 398
CHAPTER 38. A NETWORK PARSING SCHEME 400
1. INTRODUCTION 400
2. AN OVERVIEW OF THE NET-CLAUSE LANGUAGE 400
3. THE PARSING SCHEME 401
4. EXAMPLES 402
5. CONCLUSION 405
REFERENCES 406
APPENDIX 1: NET-CLAUSE CODE OF THE EXAMPLE NETWORK 407
APPENDIX 2: EXAMPLES IN PARSING 408
CHAPTER 39. HOW TO DEAL INTELLIGENTLY WITH THE UNEXPECTED ? 410
Abstract 410
Introduction 410
1. Previous work 411
2. System composition and architecture 412
3. The system's knowledge 413
4. The pilot and the sub-pilots 416
Conclusion 418
References 418
PART 5: IMAGE UNDERSTANDING AND COMPUTER VISION 420
CHAPTER 40. KNOWLEDGE-BASED INTERPRETATION OF BIOPHYSICAL IMAGES 422
1. INTRODUCTION 422
2. THE ARCHITECTURE OF THE SYSTEM ISIA 423
3. INFORMATION EXTRACTION AND KNOWLEDGE REPRESENTATION 425
4. CONCLUSIONS 428
REFERENCES 429
APPENDIX 1: EXAMPLE FOR COMPOSITE LINE AND FRAGMENTS OF ITS REPRESENTATION 430
CHAPTER 41. COMPUTER VISION AND STOCHASTIC GEOMETRY 432
1. INTRODUCTION 432
2. SYSTEM'S STRUCTURE AND RECOGNITION INVARIANT FEATURES 433
3. SCANNING TRAJECTORY PROPERTIES 435
4. DECISION PROCEDURES 436
5. SYSTEMS' VARIANTS 437
6. CONCLUSIONS 437
REFERENCES 438
CHAPTER 43. QUANTITATIVE ECOLOGICAL OPTICS 440
1. INTRODUCTION 440
2. GIBSON'S ECOLOGICAL OPTICS 441
3. MARR'S MODEL OF EARLY VISUAL PROCESSING 442
4. FRACTAL IMAGE MODELS 444
5. SIMULATED NEURAL NETWORKS 445
6. CONCLUSION 447
REFERENCES 447
AUTHOR INDEX 450

Produkt-Details

• Erscheint lt. Verlag: 22.1.2016
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• ISBN-10: 1-4832-9778-0 / 1483297780
• ISBN-13: 978-1-4832-9778-1 / 9781483297781