Artificial Intelligence V (eBook)

Methodology, Systems, Applications

B. du Boulay, V. Sgurev (Herausgeber)

eBook Download: PDF

2014 | 1. Auflage
290 Seiten
Elsevier Science (Verlag)
978-1-4832-9779-8 (ISBN)

Infos

Recent results and ongoing research in Artificial Intelligence are described in this book, with emphasis on fundamental questions in several key areas: machine learning, neural networks, automated reasoning, natural language processing, and logic methods in AI. There are also more applied papers in the fields of vision, architectures for KBS, expert systems and intelligent tutoring systems. One of the changes since AIMSA'90 has been the increased numbers of papers submitted in the fields of machine learning, neural networks and hybrid systems.One of the special features of the AIMSA series of conferences is their coverage of work across both Eastern and Western Europe and the former Soviet Union as well as papers from North America. AIMSA'92 is no exception and this volume provides a unique multi-cultural view of AI.

Inhalt

Front Cover 1
Artificial Intelligence V: Methodology, Systems, Applications 4
Copyright Page 5
Table of Contents 12
FOREWORD 6
ACKNOWLEDGEMENTS 8
CHAIRMAN OF THE CONFERENCE 10
PART I: 
16 
CHAPTER 1. 
18 
1. INTRODUCTION 18
2. BACKGROUND 19
3. SIMILARITY IN CONTEXT 20
4. TYPES OF SIMILARITY IN ANALOGICAL REASONING 21
5. COMPUTATION OF SIMILARITY IN THE DUAL ARCHITECTURE 22
6. EXPLANATION OF EXPERIMENTAL FACTS 24
7. CONCLUSIONS 26
ACKNOWLEDGEMENTS 26
REFERENCES 26
Chapter 2. 
28 
1. INTRODUCTION 28
2. FORMULATION OF 
29 
3. PROBABILISTIC INFERENCE IN DB - NET AS DIRECTED TREE 30
4. PROBABILISTIC INFERENCE IN SINGLY CONNECTED DB-NETS 35
5. CONCLUSION 38
6. REFERENCES 38
Chapter 3. 
40 
1. 
40 
2. 
41 
3. 
42 
4. 
43 
5. 
44 
6. 
48 
References 49
Chapter 4. 
50 
0. INTRODUCTION 50
1. THE PLANNING MODEL 51
2. FROM NONLINEAR/PARALLEL PLAN DESCRIPTION TO PLAN 
53 
3. CORRECTNESS OF PLAN OBJ DESCRIPTIONS 57
4. CONCLUSIONS 58
5. REFERENCES 59
PART 
60 
Chapter 5. 
62 
1 Introduction and motivation 62
2 Basics of logic programming 65
3 Modular knowledge bases 65
4 An approach to structured knowledge bases 69
5 Further research 70
References 70
CHAPTER 
72 
1. 
72 
2. 
73 
3. 
79 
4. 
80 
5. 
80 
REFERENCES 81
Chapter 7. 
82 
1. INTRODUCTION 82
2. DETECTION OF CONTRADICTIONS 83
3. BASIC FEATURES OF THE REASONING ON THE BASIS OF AN INCONSISTENT KNOWLEDGE 85
4. GRAPHICAL INTERPRETATION OF THE INFERENCE PROCESS 85
5. WAYS FOR SETTING UP THE HEURISTIC ESTIMATIONS 88
6. EXPERIMENTS, RESULTS AND PERSPECTIVES 89
7. CONCLUSIONS 90
7. REFERENCES 90
Chapter 8. 
92 
1. Introduction 92
2. Inference Relations on the Lattice of Valuations 93
3. An Application of the Framework 94
4. Linking Logics to Inference Relations 95
5· Monotonicity 97
6. Conclusion 99
7. Acknowledgements 99
8. References 99
PART III: 
100 
Chapter 9. 
102 
1. 
102 
2. 
103 
3. 
105 
4. 
106 
5. 
110 
Acknowledgements 111
References 111
Chapter 10. 
112 
I. Introduction 112
II. Space Fragmenting Description 113
III. 
115 
IV. Conclusion 119
REFERENCES 119
Chapter 11. 
120 
1. INTRODUCTION 120
2. SUPERVISED CONCEPT LEARNING AND GENETIC ALGORITHMS 121
3. SYSTEM DESCRIPTION 122
4. MORE EXPERIMENTS 125
5. SUMMARY 128
References 129
Chapter 12. 
130 
1. INTRODUCTION 130
2 . SCALE INDUCTION: THE BASEMENT 131
3 . FORMAL DESCRIPTION OF SCALE INDUCTION 133
4 . IMPLEMENTATION 136
5. CONCLUSION AND FURTHER DEVELOPMENTS 137
6. REFERENCES 138
APPENDIX 138
Chapter 13. 
140 
1. Introduction 140
2. Classification with independent classifiers 141
3. Special cases 142
4. The influence of dependance on classification accuracy 143
5. Conclusions 144
References 145
PART IV: 
146 
Chapter 14. Applying Fast Optimization Methods for Supervised Learning in Feedforward Neural 
148 
1. INTRODUCTION 148
2. BASICS 149
3. THE NEW APPROACH 150
4. IMPLEMENTATION 153
5. CONCLUSIONS 154
ACKNOWLEDGMENTS 154
REFERENCES 154
Chapter 15. 
156 
1. INTRODUCTION 156
2. A HYBRID CONNECTIONIST RULE-BASED ENVIRONMENT AND ITS APPLICABILITY TO TEMPORAL PROGNOSIS 157
3. A CONNECTIONIST PROGNOSTIC MODEL 158
4. THE HIGHER, SYMBOLIC LEVEL OF THE HYBRID PROGNOSTIC SYSTEM 161
5. AN EXPERT SYSTEM FOR AN AGRICULTURAL INSECT PROGNOSIS 161
6. CONCLUSIONS 162
7. ACKNOWLEDGEMENTS 163
8. REFERENCES 163
PART V: 
164 
Chapter 16. 
166 
1. INTRODUCTION 166
2. OVERVIEW OF THE DD-RULE FORMALISM 167
3. GRAMMAR REPRESENTATION BY MEANS OF DD-RULES 168
4. THE PARSING METHOD 170
5. RELATED WORK 173
6. CONCLUSION 173
7. REFERENCES 174
Chapter 17. 
176 
1. INTRODUCTION 176
2. WORD ORDER AND LOGIC GRAMMARS 177
3. FLEXIBLE WORD ORDER GRAMMAR 177
4. AN EXAMPLE FROM BULGARIAN 179
5. TWO IMPLEMENTATIONS 180
6. CONCLUSION 183
7. REFERENCES 183
APPENDIX 184
Chapter 18. 
186 
1. 
186 
2. 
187 
3. 
189 
4. 
190 
5. 
192 
6. 
194 
7. 
194 
8. 
194 
References 195
Chapter 19. 
196 
1. 
196 
2. 
197 
3. 
199 
4. 
200 
5. 
202 
6. 
204 
References 204
PART VI: KNOWLEDGE BASED SYSTEMS 
206 
CHAPTER 
208 
1. Introduction 208
2. An example SGES architecture 209
3. REFLOG 210
4. Meta theory 212
5· Summary 216
References 216
Chapter 21. 
218 
1. INTRODUCTION 218
2. THE GENERAL MODEL OF SYSTEMS 219
3. RELATIONS AND METHODS 220
4. PROBLEM SOLVING WITH SYSTEMS 222
5. NEURAL NETWORKS AS SYSTEMS 225
6. CONCLUSIONS 227
REFERENCES 227
Chapter 22. 
228 
1. INTRODUCTION 228
2. CONSTRAINT REPRESENTATION IN COPE 229
3. THE INTEGRATION OF CONSTRAINTS AND OBJECTS 235
4. CONCLUSIONS 235
REFERENCES 236
Chapter 23. 
238 
1. 
238 
2. 
239 
3. 
242 
4. 
244 
5. 
245 
6. 
246 
References 247
PART 
248 
Chapter 24. 
250 
1. INTRODUCTION 250
2. A SYNTHESIS-BASED APPROACH 251
3. A VISIBLE PROGRAMMING DOMAIN 251
4. AUTOMATIC TUTORING 252
5. IMMEDIATE FEEDBACK 253
6. LEARNING FROM EXAMPLES 254
7. THE IMPLEMENTATION 254
8. ACKNOWLEDGEMENT 258
REFERENCES 258
CHAPTER 25. 
262 
1. INTRODUCTION 262
2. SOFTWARE COST MODEL 263
3. KNOWLEDGE BASE 265
4. SYSTEM ARCHITECTURE 266
5. CONCLUSION 267
6. REFERENCES 268
Chapter 26. 
270 
1. 
270 
2. 
271 
3. 
273 
4. 
273 
5. 
277 
6. 
279 
References 279
Chapter 27. 
280 
1. 
280 
2. STRUCTURING AND REPRESENTATION OF CASTING KNOWLEDGE IN ISIA 281
3. STAGES OF INFORMATION EXTRACTION FROM IMAGES 283
4. IMPLEMENTATION 286
5. 
287 
6. 
287 
AUTHOR INDEX 290

Produkt-Details

• Erscheint lt. Verlag: 28.6.2014
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Netzwerke
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• ISBN-10: 1-4832-9779-9 / 1483297799
• ISBN-13: 978-1-4832-9779-8 / 9781483297798