: Longbing Cao
: Metasynthetic Computing and Engineering of Complex Systems
: Springer-Verlag
: 9781447165514
: Advanced Information and Knowledge Processing
: 1
: CHF 47.70
:
: Informatik
: English
: 360
: Wasserzeichen/DRM
: PC/MAC/eReader/Tablet
: PDF
Provides a comprehensive overview and introduction to the concepts, methodologies, analysis, design and applications of metasynthetic computing and engineering. The author:• Presents an overview of complex systems, especially open complex giant systems such as the Internet, complex behavioural and social problems, and actionable knowledge discovery and delivery in the big data era.• Discusses ubiquitous intelligence in complex systems, including human intelligence, domain intelligence, social intelligence, network intelligence, data intelligence and machine intelligence, and their synergy through metasynthetic engineering.• Explains the concept and methodology of human-centred, human-machine-cooperated qualitative-to-quantitative metasynthesis for understanding and managing open complex giant systems, and its computing approach: metasynthetic computing.• Introduces techniques and tools for analysing and designing problem-solving systems for open complex problems and systems. Metasynthetic Computing and Engineering uses the systematology methodology in addressing system complexities in open complex giant systems, for which it may not only be effective to apply reductionism or holism. The book aims to encourage and inspire discussions, design, implementation and reflection of effective methodologies and tools for computing and engineering open complex systems and problems. Researchers, research students and practitioners in complex systems, artificial intelligence, data science, computer science, and even system science, cognitive science, behaviour science, and social science, will find this book invaluable.
Preface6
Contents8
Chapter 1: Complex Systems16
1.1 Introduction16
1.2 System Complexities16
1.3 System Transparency20
1.3.1 Black Boxes20
1.3.2 White Boxes21
1.3.3 Glass Boxes21
1.3.4 Grey Boxes21
1.4 System Classification22
1.5 Complex Agent Systems24
1.5.1 Multiagent Systems24
1.5.1.1 What Are Multiagent Systems24
1.5.1.2 Multiagent System Research Map25
1.5.2 Large-Scale Systems28
1.5.3 Large-Scale Multiagent Systems28
1.5.3.1 Concepts and Issues28
1.5.3.2 How Are ULS Systems Different? [40]29
1.5.3.3 Major Research Issues30
1.5.4 Open Complex Agent Systems32
1.5.4.1 Multiagent System Classification32
1.5.4.2 Open Complex Agent Systems33
1.6 Hybrid Intelligent Systems34
1.6.1 Concept34
1.6.2 Hybridization Strategies35
1.6.3 Design Strategies37
1.6.4 Typical Hybrid Applications38
1.7 Evolution of Intelligent Systems40
1.8 Open Giant Intelligent Systems44
1.9 Computing and Engineering Complex Systems46
1.10 Summary48
References48
Chapter 2: Ubiquitous Intelligence52
2.1 Introduction52
2.2 Data Intelligence53
2.2.1 What Is Data Intelligence?53
2.2.2 Aims of Involving Data Intelligence53
2.2.3 Aspects of Data Intelligence54
2.3 Domain Intelligence55
2.3.1 What Is Domain Intelligence?55
2.3.2 Aims of Involving Domain Intelligence55
2.3.3 Aspects of Domain Intelligence56
2.4 Network Intelligence56
2.4.1 What Is Network Intelligence?56
2.4.2 Aims of Involving Network Intelligence57
2.4.3 Aspects of Network Intelligence57
2.5 Human Intelligence58
2.5.1 What Is Human Intelligence?58
2.5.2 Aims of Involving Human Intelligence58
2.5.3 Aspects of Human Intelligence59
2.6 Organizational Intelligence60
2.6.1 What Is Organizational Intelligence?60
2.6.2 Aims of Involving Organizational Intelligence60
2.6.3 Aspects of Organizational Intelligence61
2.7 Social Intelligence61
2.7.1 What Is Social Intelligence?61
2.7.2 Aims of Involving Social Intelligence62
2.7.3 Aspects of Social Intelligence62
2.8 Metasynthesis of Ubiquitous Intelligence63
2.9 Summary64
References64
Chapter 3: System Methodologies66
3.1 Introduction66
3.2 Reductionism67
3.3 Holism68
3.4 Systematology68
3.5 Summary70
References70
Chapter 4: Computing Paradigms72
4.1 Introduction72
4.2 Objects and Object-Oriented Methodology73
4.3 Components and Component-Based Methodology73
4.4 Services and Service-Oriented Methodology74
4.5 Agents and Agent-Oriented Methodology75
4.5.1 Goal-Oriented Requirements Analysis76
4.5.2 Agent-Oriented Software Engineering77
4.5.2.1 MaSE78
4.5.2.2 MESSAGE78
4.5.2.3 TROPOS78
4.5.2.4 GAIA79
4.5.3 Issues in Agent-Oriented Software Engineering80
4.6 Relations Among Agents, Objects, Components, and Services81
4.7 Autonomic Computing82
4.8 Organizational Computing85
4.9 Behavior Computing86
4.10 Social Computing89
4.11 Cloud/Service Computing92
4.12 Metasynthetic Computing93
References93
Chapter 5: Metasynthesis96
5.1 Introduction96
5.2 Open Complex Giant Systems96
5.3 OCGS System Complexities100
5.4 Knowledge and Intelligence Emergence102
5.5 Theoretical Framework of Metasynthesis108
5.6 Problem-Solving Process in M-Space110
5.7 Social Cognitive Intelligence Emergence in M-Space113
5.7.1 Individual Cognitive Model113
5.7.2 Social Cognitive Interaction Model114
Member norm: sample norms, rules, and policies for social cognitive interaction115
Interaction protocol: sample codes of conduct for social cognitive interaction115
Interaction protocol: sample codes of conduct for social cognitive interaction115
Interaction operator: sample operators representing interaction modes116
5.7.3 Cognitive Intelligence Emergence116
5.8 Thinking Pitfalls in M-Interactions117
Strategy: avoiding dependent thinking in M-interactions117
Strategy: avoiding over-divergent thinking in M-interactions118
Strategy: avoiding group thinking in M-interactions119
Strategy: avoiding rigid thinking in M-interactions119
5.9 M-Computing: Engineering OCGS120
5.10 Discussions121
References123
Chapter 6: OSOAD Methodology126
6.1 Introduction126
6.2 Organizational Abstraction126
6.2.1 Actors127
6.2.2 Environment128
6.2.3 Interaction128
6.2.4 Organizational Rules129
6.2.5 Organizational Structure129
6.2.6 Organizational Goal130
6.2.7 Organizational Dynamics130
6.3 Organization-Oriented Analysis131
6.3.1 Challenges fo