CONTENTS
List of Contributors = xi
Foreword by Michael Arbib = xiii
Preface = xvii
1 An Introduction; On Symbolic Processing in Neural Networks = 1
1 Introduction = 1
2 Brief Review = 4
3 Existing Approaches = 5
4 Issues and Difficulties = 7
5 Future Directions, Or Where Should We Go From Here? = 11
6 Overview of the Chapters = 12
7 Summary = 15
References = 16
Part I LOCALIST ARCHITECTURES = 19
2 Complex Sympol - Processing in Conposit, A Transiently Localist Connectionist Archiecture = 21
1 Introduction = 21
2 The Johnson-Laird Theory and Its Challenges = 22
3 Mental Models in Conposit = 31
4 Connectionist Realization of Conposit = 48
5 Coping with the Johnson-Laird Chalenge = 54
6 Simulation Runs = 58
7 Discussion = 62
8 Summary = 64
References = 65
3 A Structured Connectionist Approach to Inferencing and Retrieval = 69
1 Introduction = 69
2 Language Understanding and Memory Retrieval Models = 74
3 Inferencing in ROBIN = 82
4 Episodic Retrieval in REMIND = 92
5 Future Work = 102
6 Summary = 110
References = 111
4 Hierarchical Architectures for Reasoning = 117
1 Introduction = 117
2 Computational Networks: A General Setting for Distributed Computations = 118
3 Type x00 Computational Networks = 126
4 Expert Systems = 129
5 Expert Networks = 133
6 Neural Networks = 140
7 Summary = 143
References = 145
Part Ⅱ DISTRIBUTED ARCHITECTURES = 151
5 Subsymbolic Parsing of Embedded Structures = 153
1 Introduction = 153
2 Overview of Subsymbolic Sentence Processing = 155
3 The SPEC Architecture = 158
4 Experiments = 166
5 Discussion = 177
6 Summary = 179
References = 180
6 Towards Instructable Connectionist Systems = 187
1 Introduction = 187
2 Systematic Action = 192
3 Linguistic Interaction = 200
4 Learning By Instruction = 207
5 Summary = 217
References = 220
7 An Internal Report for Connectionists = 223
1 Introduction = 223
2 The Origins of Connectionist Representation = 225
3 Representation and Decision Space = 229
4 Discussion = 240
5 Summary = 242
References = 243
Part Ⅲ COMBINED ARCHITECTURES = 245
8 A Two-Level Hybrid Architecture for Structuring Knowledge for Commonsense Reasoning = 247
1 Introduction = 247
2 Developing A Two-Level Architecture = 250
3 Fine-Tuning the Structure = 255
4 Experiments = 264
5 Comparisons with Other Approaches = 274
6 Summary = 275
References = 278
9 A Framework for Integrating Relational and Associational Knowledge for Comprehension = 283
1 Introduction = 283
2 Overview of LeMICON = 287
3 Text Comprehension = 289
4 Encoding Semantic Memory = 296
5 Representation of Semantic Constraints = 298
6 Experiments and Results = 299
7 Algorithm = 308
8 Summary = 313
References = 315
10 Examining a Hybrid Connectionist / Symbolic System for the Analysis of Ballistic Signals = 319
1 Introduction = 319
2 Related Work in Hybrid Systems = 321
3 Description of the SCRuFFY Architecture = 322
4 Aalysis of Ballistic Signals = 325
5 Future Work = 333
6 Conclusion = 334
References = 347
Part Ⅳ COMMENTARIES = 349
11 Symbolic Artificial lntelligence and Numeric Artificial Neural Networks ; Towards a Resolution of the Dichotomy = 351
1 Introduction = 351
2 Shared Foundations of SAI and NANN = 353
3 Knowledge Representation Revisited = 356
4 A Closer Look at SAI and NANN = 360
5 Integration of SAI and NANN = 374
6 Summary = 375
References = 378
12 Connectionist Natural Language Processing ; A Status Report = 389
1 Introduction = 389
2 Dynamic Bindings = 391
3 Functional Bindings and Structured Pattern Matching = 397
4 Encoding and Accessing Recursive Structures = 398
5 Forming Lexical Memories = 401
6 Forming Semantic and Episodic Memories = 405
7 Role of Working Memory = 407
8 Routing and Control = 408
9 Grounding Language in Perception = 413
10 Future Directions = 418
11 Conclusions = 421
References = 423
Appendix Bibliography of Connectionist Models with Symbolic Processing = 431
Author Index = 457
Subject Index = 463
About The Editors = 475
