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Produktbild: Parallel Population and Parallel Human

Parallel Population and Parallel Human A Cyber-Physical Social Approach

Aus der Reihe IEEE Series on Systems Science and Engineering

151,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

27.06.2023

Verlag

John Wiley & Sons Inc

Seitenzahl

352

Maße (L/B/H)

22,9/15,2/2,1 cm

Gewicht

630 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-1-394-18189-6

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

27.06.2023

Verlag

John Wiley & Sons Inc

Seitenzahl

352

Maße (L/B/H)

22,9/15,2/2,1 cm

Gewicht

630 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-1-394-18189-6

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: GPSR Kontakt

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  • Produktbild: Parallel Population and Parallel Human
  • Preface xi
     
    Acknowledgments xv
     
    1 From Behavioral Analysis to Prescription 1
     
    1.1 Social Intelligence 1
     
    1.2 Human-Machine Interaction 4
     
    1.3 From Behavior Analysis to Prescription 6
     
    1.4 Parallel Population and Parallel Human 9
     
    1.5 Central Themes and Structure of this Book 11
     
    References 13
     
    2 Basic Population Synthesis 17
     
    2.1 Problem Statement and Data Sources 18
     
    2.1.1 Cross-Classification Table 18
     
    2.1.2 Sample 21
     
    2.1.3 Long Table 22
     
    2.2 Sample-Based Method 23
     
    2.2.1 Iterative Proportional Fitting Synthetic Reconstruction 23
     
    2.2.2 Combinatorial Optimization 24
     
    2.2.3 Copula-Based Synthesis 26
     
    2.3 Sample-Free Method 30
     
    2.4 Experiment Results 37
     
    2.4.1 Copula-Based Population Synthesis 37
     
    2.4.2 Joint Distribution Inference 43
     
    2.5 Conclusions and Discussions 52
     
    References 53
     
    3 Synthetic Population with Social Relationships 55
     
    3.1 Household Integration in Synthetic Population 56
     
    3.2 Individual Assignment 60
     
    3.2.1 Heuristic Allocation 62
     
    3.2.2 Iterative Allocation 65
     
    3.3 Heuristic Search 67
     
    3.4 Joint Distribution Fitting 70
     
    3.5 Deep Generative Models 75
     
    3.6 Population Synthesis with Multi-social Relationships 78
     
    3.6.1 Limitations of IPU Algorithm 78
     
    3.6.2 Population with Multi-social Relationships 85
     
    3.7 Conclusions and Discussions 93
     
    References 95
     
    4 Architecture for Agent Decision Cycle 97
     
    4.1 Parallel Humans in Human-Machine Interactive Systems 98
     
    4.2 Why and What Is the Cognitive Architecture? 100
     
    4.3 Architecture for Artificial General Intelligence 103
     
    4.4 Architecture for Control 110
     
    4.5 Architecture for Knowledge Discovery 113
     
    4.6 Architecture for Computational Neuroscience 116
     
    4.7 Architecture for Pattern Recognition 121
     
    4.8 Other Representative Architecture 123
     
    4.9 TiDEC: A Two-Layered Integrated Cycle for Agent Decision 129
     
    4.10 Conclusions and Discussions 134
     
    References 135
     
    5 Evolutionary Reasoning 141
     
    5.1 Knowledge Representation 142
     
    5.2 Evolutionary Reasoning Using Causal Inference 147
     
    5.3 Learning Fitness Function from Expert Decision Chains 156
     
    5.4 Conclusions and Discussions 158
     
    References 158
     
    6 Knowledge Acquisition by Learning 163
     
    6.1 Foundation of Knowledge Repository Learning 164
     
    6.2 Knowledge Acquisition Based on Self-Supervised Learning 167
     
    6.3 Adaptive Knowledge Extraction for Data Stream 170
     
    6.3.1 Neural-Symbolic Learning 171
     
    6.3.2 Explanation of Deep Learning 176
     
    6.4 Experiment on Travel Behavior Learning 183
     
    6.5 Conclusions and Discussions 194
     
    References 195
     
    7 Agent Calibration and Validation 199
     
    7.1 Model Calibration for Agent 199
     
    7.2 Calibration Based on Optimization 202
     
    7.3 Calibration Based on Machine Learning 209
     
    7.4 Calibration Based on Cybernetics 214
     
    7.5 Calibration Using Variational Auto-Encoder 227
     
    7.6 Conclusions and Discussions 233
     
    References 233
     
    8 High-Performance Computing for Computational Deliberation Experiments 237
     
    8.1 Computational Acceleration Using High-Performance Computing 237
     
    8.1.1 Spark with Hadoop 238
     
    8.1.2 MPI/OpenMP on Supercomputing 244
     
    8.2 Computational Deliberation Experiments in Cloud Computing 249
     
    8.3