Mind computation:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New Jersey
World Scientific
[2017]
|
| Schriftenreihe: | Series on intelligence science
vol. 3 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | xx, 468 Seiten Illustrationen, Diagramme |
| ISBN: | 9789813145801 |
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Datensatz im Suchindex
| _version_ | 1804177480827797504 |
|---|---|
| adam_text | Contents
About the Author vii
Preface ix
Acknowledgment xi
Chapter 1 Introduction 1
1.1 Mind.......................................................... 1
1.2 Philosophy Issues of Mind..................................... 3
1.3 Biological Basis of Mind...................................... 6
1.4 Intelligence Science Issues of Mind........................... 8
1.4.1 Working mechanism of brain neural network.............10
1.4.2 Perception process and perception theory..............11
1.4.3 Memory.............................................. 12
1.4.4 Learning .............................................13
1.4.5 Cognitive mechanisms of language processing...........14
1.4.6 Cognitive mechanisms of thought.......................16
1.4.7 Intelligence development..............................16
1.4.8 Emotion system........................................17
1.4.9 Consciousness ........................................18
1.4.10 Mind model............................................18
1.5 The Structure of Mind.........................................20
1.6 The Modularity of Mind........................................22
1.7 The Society of Mind...........................................25
1.8 Automata Theory...............................................27
1.8.1 Overview..............................................27
1.8.1.1 Abstract theory..............................29
1.8.1.2 Structure theory ............................29
1.8.1.3 Self-organization theory.....................30
1.8.2 Finite state automata (FSA)...........................30
1.8.3 Probabilistic automata................................32
xiii
xiv Contents
1.8.4 Cellular automata (CA)................................32
1.9 Turing Machine................................................34
1.10 Computational Theory of Mind..................................35
Chapter 2 Mind Model CAM 43
2.1 Introduction..................................................43
2.2 Criteria of Mind Modeling.....................................47
2.2.1 Agile action..........................................47
2.2.2 Real-time.............................................48
2.2.3 Adaptive behavior ....................................48
2.2.4 Large-scale knowledge base............................48
2.2.5 Dynamic action........................................49
2.2.6 Knowledge integration.................................49
2.2.7 Natural language......................................50
2.2.8 Consciousness ........................................50
2.2.9 Learning .............................................51
2.2.10 Development...........................................51
2.2.11 Evolution.............................................51
2.2.12 Brain.................................................52
2.3 Cognitive Mind Modeling.......................................52
2.3.1 Physical symbol system ...............................52
2.3.2 ACT-R ................................................53
2.3.3 Soar..................................................54
2.4 Connectionism-based Mind Modeling.............................58
2.4.1 Connectionism.........................................58
2.4.1.1 Large-scale parallel processing...............59
2.4.1.2 Content-based addressing .....................59
2.4.1.3 Distributed storage...........................59
2.4.1.4 Adaptability .................................60
2.4.1.5 Fault tolerance...............................60
2.4.2 Adaptive Resonance Theory.............................60
2.5 Agent Mind Modeling...........................................64
2.6 CAM Architecture..............................................66
2.7 CAM Cognitive Cycle...........................................71
2.7.1 Perception phase......................................72
2.7.2 Motivation phase.................................... 72
2.7.3 Action planning phase.................................72
Contents xv
Chapter 3 Memory 73
3.1 Overview........................................................73
3.2 Basis of the DDL................................................75
3.2.1 Notations..............................................75
3.2.2 Semantics of the DDL...................................77
3.2.3 Inference in the DDL...................................77
3.3 Long-term Memory................................................79
3.3.1 Semantic memory........................................81
3.3.1.1 Hierarchical network model.....................81
3.3.1.2 Spreading activation model.....................83
3.3.1.3 Set theoretic model............................84
3.3.1.4 Feature comparison model.......................85
3.3.1.5 Human association memory.......................87
3.3.1.6 ELINOR model...................................89
3.3.1.7 Ontology memory model..........................89
3.3.2 Episodic memory........................................90
3.3.3 Procedural memory......................................94
3.4 Short-term Memory...............................................96
3.4.1 Short-term memory encoding.............................97
3.4.2 Information extraction.................................98
3.4.2.1 The classical research by Sternberg............99
3.4.2.2 Direct access model............................99
3.4.2.3 Dual model....................................100
3.4.3 Short-term memory in CAM..............................102
3.4.3.1 Belief........................................103
3.4.3.2 Target........................................103
3.4.3.3 Intention.....................................104
3.5 Working Memory ................................................104
3.5.1 Models of working memory..............................104
3.5.2 Working memory and reasoning..........................106
3.5.3 Neural mechanism of working memory....................108
3.6 Theory of Forgetting...........................................109
3.7 Physiological Mechanism of Memory..............................115
3.8 Theory of Memory-Prediction....................................118
3.8.1 Constant characterization.............................119
xvi Contents
3.8.2 Structure of cerebral cortex .........................120
3.8.3 How does the cerebral cortex work.....................121
Chapter 4 Consciousness 123
4.1 Overview .....................................................123
4.1.1 Base elements of consciousness . .....................127
4.1.2 The attribute of consciousness .......................132
4.2 Theory of Consciousness ......................................133
4.2.1 The theater of consciousness .........................133
4.2.2 Reductionism..........................................137
4.2.3 Theory of neuronal group selection ...................142
4.2.4 Quantum theories.................................... 144
4.2.5 Block model of consciousness..........................147
4.2.6 Information integration theory .................... . . 148
4.3 Attention.....................................................151
4.3.1 Attention functions...................................151
4.3.2 Selective attention ................................ 155
4.3.3 Attention distribution................................161
4.3.4 Attention system......................................162
4.4 Metacognition.................................................163
4.4.1 Metacognitive knowledge ..............................163
4.4.2 Metacognitive experience..............................164
4.4.3 Metacognitive monitoring .............................164
4.4.4 Metacognition training................................164
4.5 Motivation....................................................165
4.5.1 Overview............................................ 165
4.5.2 Theory of motivation..................................167
4.6 Consciousness Subsystem in CAM................................174
4.6.1 Awareness module......................................174
4.6.2 Attention module......................................176
4.6.3 Global workspace module...............................177
4.6.4 Motivation module.....................................178
4.6.5 Metacognitive module..................................181
4.6.6 Introspective learning module.........................181
Chapter 5 Visual Perception 183
5.1 Visual Cortex Area . .........................................183
Contents xvii
5.2 Visual Computation Theory.................................... 185
5.2.1 Marr’s visual computation theory .....................185
5.2.2 Gestalt vision theory.................................190
5.2.3 Dual visual pathway...................................191
5.2.4 Topological vision theory.............................192
5.3 Feature Binding...............................................193
5.3.1 Temporal synchronization theory.......................194
5.3.2 Formal model of feature binding.......................195
5.3.3 Feature integration theory ...........................195
5.3.4 Neural network model..................................196
5.4 Object Recognition............................................198
5.4.1 Visual representation.................................198
5.4.2 Object low-level feature extraction...................199
5.4.3 Relation encoding.....................................200
5.4.4 Learning recognition network..........................201
5.4.5 Link search...........................................204
5.5 Visual Space Cognition .......................................205
5.6 Visual Effective Coding.......................................211
Chapter 6 Motor Control 219
6.1 The Neural Structure of Motor Control.........................219
6.2 Motor Cortex..................................................221
6.3 The Basal Ganglia.............................................223
6.4 Motor Control Pathway.........................................229
6.5 EEG Signal Analysis...........................................234
6.5.1 EEG signal sorting....................................234
6.5.2 EEG signal analytical method..........................236
6.6 Encoding Motor................................................239
6.6.1 Overview..............................................239
6.6.2 Entropy encoding theory...............................242
6.6.3 Bayesian neuronal population encoding.................246
6.6.4 Bayesian neuronal population decoding.................247
6.7 Brain-Computer Interface......................................249
6.7.1 Overview..............................................249
6.7.2 Brain—Computer interface technology...................251
6.7.3 P300 Brain—computer interface system..................255
6.8 Brain-Computer Integration....................................259
xviii Contents
Chapter 7 Language Cognition 263
7.1 Mental Lexicon................................................ 263
7.2 Perceptual Analysis of Language Input...........................265
7.2.1 Spoken language input...................................265
7.2.2 Speech coding ..........................................267
7.2.3 Rhythm perception.......................................268
7.2.4 Written input...........................................276
7.2.5 Word recognition........................................280
7.2.6 Speech generation ......................................280
7.3 Chomsky’s Formal Grammar........................................283
7.3.1 Phrase structure grammar................................283
7.3.2 Context-sensitive grammar...............................284
7.3.3 Context-free grammar (CFG)..............................285
7.3.4 Regular grammar.........................................287
7.4 Augmented Transition Networks ..................................289
7.5 Conceptual Dependency Theory.................................. 292
7.6 Language Understanding..........................................295
7.6.1 Overview.............................................. . 295
7.6.2 Development stage.......................................298
7.6.3 Rule-based analysis method..............................301
7.6.4 Statistical model based on Corpus.......................305
7.6.5 Machine learning method.................................308
7.7 Functional Area of Brain........................................312
7.7.1 Classical function area.................................312
7.7.2 Semantic-related functional area........................314
7.7.3 Phonological-related functional area....................315
7.7.4 Spelling-related functional area .......................315
7.7.5 Bilingual brain functional areas .......................315
7.8 Neural Model of Language Understanding..........................316
7.8.1 Aphasia.................................................316
7.8.2 Classical localization model............................318
7.8.3 Memory-integration-control model........................321
Chapter 8 Learning 325
8.1 Introduction ...................................................325
8.2 Reinforcement Learning..........................................327
8.2.1 RL model................................................327
8.2.2 Q learning .............................................332
Contents xix
8.2.3 Partial observation reinforcement learning...........334
8.2.4 Motivated reinforcement learning (MRL)...............336
8.2.5 Reinforcement learning of Soar system................345
8.3 Deep Learning................................................348
8.3.1 Introduction.........................................348
8.3.2 Human brain visual mechanism.........................349
8.3.3 Autoencoder..........................................350
8.3.4 Restricted Boltzmann machine.........................352
8.3.5 Deep belief networks.................................355
8.3.6 Convolutional neural networks........................357
8.4 Introspective Learning.......................................364
8.4.1 Introduction.........................................364
8.4.2 General model of introspection learning..............366
8.4.3 Meta-reasoning of introspection learning ............368
8.4.4 Failure classification...............................369
8.4.5 Case-based reasoning in the introspective
process..............................................371
8.5 Brain Cognitive Data Analysis................................372
8.5.1 Brain function imaging...............................372
8.5.2 Brain nerve semantics ...............................372
8.5.3 Brain functional connectivity analysis...............375
Chapter 9 Brain-Like Computing 379
9.1 Overview.....................................................379
9.2 Blue-Brain Project...........................................381
9.2.1 Brain neural network.................................381
9.2.2 Cerebral cortex model................................382
9.2.3 Super computing simulation...........................387
9.3 Human Brain Project of the EU................................390
9.3.1 Introduction.........................................390
9.3.2 Spike-timing-dependent plasticity . .................395
9.3.3 Unified brain model..................................398
9.4 The US Brain Project.........................................400
9.4.1 Human connectome project.............................400
9.4.2 MoNETA...............................................401
9.4.3 Neurocore chip.......................................403
9.4.4 HP memristor.........................................404
9.5 Brain Simulation System Spaun................................406
xx Contents
9.6 Neuromorphic Chip............................................410
9.6.1 The development history of neuromorphic chip.........410
9.6.2 IBM’s TrueNorth neuromorphic system..................412
9.6.3 British SpiNNaker....................................416
9.7 Development Roadmap of Intelligence Science..................417
9.7.1 Elementary brain-like computing......................418
9.7.2 Advanced brain-like computing........................422
9.7.3 Super-brain computing................................424
References 429
Index
453
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| indexdate | 2024-07-10T07:48:45Z |
| institution | BVB |
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| language | English |
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| spelling | Shi, Zhongzhi Verfasser (DE-588)1014634504 aut Mind computation Zhongzhi Shi (Chinese Academy of Sciences, China) New Jersey World Scientific [2017] xx, 468 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Series on intelligence science vol. 3 Computational intelligence Cognition Kognition (DE-588)4031630-0 gnd rswk-swf Künstliche Intelligenz (DE-588)4033447-8 gnd rswk-swf Künstliche Intelligenz (DE-588)4033447-8 s Kognition (DE-588)4031630-0 s DE-604 Series on intelligence science vol. 3 (DE-604)BV040664920 3 Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029690693&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Shi, Zhongzhi Mind computation Series on intelligence science Computational intelligence Cognition Kognition (DE-588)4031630-0 gnd Künstliche Intelligenz (DE-588)4033447-8 gnd |
| subject_GND | (DE-588)4031630-0 (DE-588)4033447-8 |
| title | Mind computation |
| title_auth | Mind computation |
| title_exact_search | Mind computation |
| title_full | Mind computation Zhongzhi Shi (Chinese Academy of Sciences, China) |
| title_fullStr | Mind computation Zhongzhi Shi (Chinese Academy of Sciences, China) |
| title_full_unstemmed | Mind computation Zhongzhi Shi (Chinese Academy of Sciences, China) |
| title_short | Mind computation |
| title_sort | mind computation |
| topic | Computational intelligence Cognition Kognition (DE-588)4031630-0 gnd Künstliche Intelligenz (DE-588)4033447-8 gnd |
| topic_facet | Computational intelligence Cognition Kognition Künstliche Intelligenz |
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