A guide to two types of transcendence of academic borders necessary to the understanding and modeling of brain function: Technical transcendence needed to make intelligent machines, and transcendence of cross-disciplinary boundaries to incorporate less technical and more abstract, cognitive aspects of brain function into modeling.
Author(s): Tadashi Kitamura
Publisher: World Scientific Publishing Company
Year: 2001
Language: English
Pages: 323
Tags: Информатика и вычислительная техника;Искусственный интеллект;
Series Editor's Preface......Page 6
Volume Editor's Preface......Page 8
Contents......Page 12
1.1 Introduction......Page 14
1.2 Acquisition Algorithm of World Model of Robots......Page 15
1.3 Primitive Language......Page 17
1.4 Autonomous Robot: WAMOEBA-2......Page 18
1.5 Communication of WAMOEBA-2......Page 26
1.6 Model Acquisition Algorithm of WAMOEBA-2......Page 27
1.7 Diversification of Expression......Page 30
1.8 Evaluation Experiment......Page 32
1.9 Conclusion and Further Perspectives......Page 33
References......Page 34
2.1 Introduction......Page 36
2.2 Architechture(CBA)......Page 38
2.3 Criteria for Behavior Selection......Page 41
2.4 Behavior Design......Page 44
2.5 Experiments......Page 46
2.6 Discussion......Page 51
References......Page 54
3.1 Introduction......Page 56
3.2 Literary Text and Cognition......Page 59
3.3 Literary Computing......Page 61
3.4 Conclusions......Page 63
References......Page 64
4.1 Introduction......Page 66
4.2 Cerebral Cortex : the 'Pilot'......Page 68
4.3 Cerebellar Cortex : the 'Smoother Computer'......Page 73
4.4 Basal Ganglia : the 'Security' Computer......Page 80
4.5 Conclusion......Page 83
References......Page 85
5.1 Introduction: What Brain-like Functions and Principles to Implement in Intelligent Information Systems?......Page 90
5.2 The ECOS Framework......Page 96
5.3 Evolving Fuzzy Neural Networks EFuNNs......Page 99
5.4 EFuNNs as Universal Learning Machines. Local and Global Generalisation......Page 116
5.5 Conclusions and Directions for Further Research......Page 119
References......Page 121
6.1 Introduction......Page 128
6.2 State of the Art......Page 130
6.3 Several Desirable Properties and Current Limits of the Current Machines......Page 134
6.4 The Sensitive Computer......Page 135
6.5 Perception, Self-representation and Self-relating......Page 137
6.6 Relationship and Relationship Representation: Key Factors in Intelligence and Communication......Page 142
6.7 Methods to Embed Relationships......Page 149
6.8 Technical Means......Page 153
6.9 Conclusions and Future Perspectives......Page 156
References......Page 159
7.1 Introduction......Page 162
7.2 Distinction by Invalidating Distinction......Page 165
7.3 Punctuated Equilibrium Resulting Asynchronous Clock......Page 170
7.4 Origin of Time......Page 178
7.5 Conclusion......Page 191
References......Page 193
8.1 Introduction......Page 196
8.2 A Relationship between a Self-similarity and a Paradox......Page 198
8.3 Methods......Page 201
8.4 Results......Page 206
8.5 Conclusion and Future Perspective......Page 215
References......Page 217
9.1 Introduction......Page 220
9.2 Communication by Representations......Page 221
9.3 Observations of Electroencephalograms......Page 223
9.4 The Neural Basis for Intentional Action......Page 224
9.5 Linear versus Circular Causality......Page 225
9.6 A Hypothesis on the Causal Relations of Meanings and Representations......Page 226
References......Page 227
10.1 Introduction......Page 230
10.2 Function......Page 231
10.3 Representation......Page 233
10.4 Brain and Mind: Some Relations......Page 243
10.5 Conclusions......Page 245
References......Page 246
11.1 Introduction......Page 252
11.2 Intentionality and Cognitive Neuroscience......Page 254
11.3 Intentionality and Foundations of Logic after Godel......Page 276
11.4 Conclusion......Page 294
References......Page 295
About the Authors......Page 302
Keyword Index......Page 316
