Metasynthetic Computing and Engineering of Complex Systems (eBook)
XIV, 348 Seiten
Springer London (Verlag)
978-1-4471-6551-4 (ISBN)
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.
Preface 6
Contents 8
Chapter 1: Complex Systems 16
1.1 Introduction 16
1.2 System Complexities 16
1.3 System Transparency 20
1.3.1 Black Boxes 20
1.3.2 White Boxes 21
1.3.3 Glass Boxes 21
1.3.4 Grey Boxes 21
1.4 System Classification 22
1.5 Complex Agent Systems 24
1.5.1 Multiagent Systems 24
1.5.1.1 What Are Multiagent Systems 24
1.5.1.2 Multiagent System Research Map 25
1.5.2 Large-Scale Systems 28
1.5.3 Large-Scale Multiagent Systems 28
1.5.3.1 Concepts and Issues 28
1.5.3.2 How Are ULS Systems Different? [40] 29
1.5.3.3 Major Research Issues 30
1.5.4 Open Complex Agent Systems 32
1.5.4.1 Multiagent System Classification 32
1.5.4.2 Open Complex Agent Systems 33
1.6 Hybrid Intelligent Systems 34
1.6.1 Concept 34
1.6.2 Hybridization Strategies 35
1.6.3 Design Strategies 37
1.6.4 Typical Hybrid Applications 38
1.7 Evolution of Intelligent Systems 40
1.8 Open Giant Intelligent Systems 44
1.9 Computing and Engineering Complex Systems 46
1.10 Summary 48
References 48
Chapter 2: Ubiquitous Intelligence 52
2.1 Introduction 52
2.2 Data Intelligence 53
2.2.1 What Is Data Intelligence? 53
2.2.2 Aims of Involving Data Intelligence 53
2.2.3 Aspects of Data Intelligence 54
2.3 Domain Intelligence 55
2.3.1 What Is Domain Intelligence? 55
2.3.2 Aims of Involving Domain Intelligence 55
2.3.3 Aspects of Domain Intelligence 56
2.4 Network Intelligence 56
2.4.1 What Is Network Intelligence? 56
2.4.2 Aims of Involving Network Intelligence 57
2.4.3 Aspects of Network Intelligence 57
2.5 Human Intelligence 58
2.5.1 What Is Human Intelligence? 58
2.5.2 Aims of Involving Human Intelligence 58
2.5.3 Aspects of Human Intelligence 59
2.6 Organizational Intelligence 60
2.6.1 What Is Organizational Intelligence? 60
2.6.2 Aims of Involving Organizational Intelligence 60
2.6.3 Aspects of Organizational Intelligence 61
2.7 Social Intelligence 61
2.7.1 What Is Social Intelligence? 61
2.7.2 Aims of Involving Social Intelligence 62
2.7.3 Aspects of Social Intelligence 62
2.8 Metasynthesis of Ubiquitous Intelligence 63
2.9 Summary 64
References 64
Chapter 3: System Methodologies 66
3.1 Introduction 66
3.2 Reductionism 67
3.3 Holism 68
3.4 Systematology 68
3.5 Summary 70
References 70
Chapter 4: Computing Paradigms 72
4.1 Introduction 72
4.2 Objects and Object-Oriented Methodology 73
4.3 Components and Component-Based Methodology 73
4.4 Services and Service-Oriented Methodology 74
4.5 Agents and Agent-Oriented Methodology 75
4.5.1 Goal-Oriented Requirements Analysis 76
4.5.2 Agent-Oriented Software Engineering 77
4.5.2.1 MaSE 78
4.5.2.2 MESSAGE 78
4.5.2.3 TROPOS 78
4.5.2.4 GAIA 79
4.5.3 Issues in Agent-Oriented Software Engineering 80
4.6 Relations Among Agents, Objects, Components, and Services 81
4.7 Autonomic Computing 82
4.8 Organizational Computing 85
4.9 Behavior Computing 86
4.10 Social Computing 89
4.11 Cloud/Service Computing 92
4.12 Metasynthetic Computing 93
References 93
Chapter 5: Metasynthesis 96
5.1 Introduction 96
5.2 Open Complex Giant Systems 96
5.3 OCGS System Complexities 100
5.4 Knowledge and Intelligence Emergence 102
5.5 Theoretical Framework of Metasynthesis 108
5.6 Problem-Solving Process in M-Space 110
5.7 Social Cognitive Intelligence Emergence in M-Space 113
5.7.1 Individual Cognitive Model 113
5.7.2 Social Cognitive Interaction Model 114
Member norm: sample norms, rules, and policies for social cognitive interaction 115
Interaction protocol: sample codes of conduct for social cognitive interaction 115
Interaction protocol: sample codes of conduct for social cognitive interaction 115
Interaction operator: sample operators representing interaction modes 116
5.7.3 Cognitive Intelligence Emergence 116
5.8 Thinking Pitfalls in M-Interactions 117
Strategy: avoiding dependent thinking in M-interactions 117
Strategy: avoiding over-divergent thinking in M-interactions 118
Strategy: avoiding group thinking in M-interactions 119
Strategy: avoiding rigid thinking in M-interactions 119
5.9 M-Computing: Engineering OCGS 120
5.10 Discussions 121
References 123
Chapter 6: OSOAD Methodology 126
6.1 Introduction 126
6.2 Organizational Abstraction 126
6.2.1 Actors 127
6.2.2 Environment 128
6.2.3 Interaction 128
6.2.4 Organizational Rules 129
6.2.5 Organizational Structure 129
6.2.6 Organizational Goal 130
6.2.7 Organizational Dynamics 130
6.3 Organization-Oriented Analysis 131
6.3.1 Challenges for Current Organization-Related Software Engineering 131
6.3.2 What is Organization-Oriented Analysis? 132
6.4 Agent Service-Oriented Design 134
6.4.1 Agent Service, Services of Agent, and Services of Service 134
6.4.2 Why Agent Service-Oriented Design? 134
6.4.3 What is Agent Service-Oriented Design? 135
6.4.4 Agent Service-Oriented Architectural Design 138
6.4.5 Agent Service-Oriented Detailed Design 139
6.5 Building Organization and Service-Oriented Software Engineering 139
6.6 Summary 142
References 142
Chapter 7: Visual Modeling 145
7.1 Introduction 145
7.2 Actor Model 145
7.2.1 Actor Classification 145
7.2.2 Role Model 147
7.3 Environment Model 149
7.3.1 Characteristics of Agent Environment 149
7.3.2 Classification of Agent Environment 150
7.3.2.1 Physical Environment 150
7.3.2.2 Electronic Environment 151
7.3.2.3 Social Environment 151
7.3.3 POMDPAEI Model 152
7.4 Modeling Organizational Rules 152
7.4.1 Structural Rules 152
7.4.2 Problem-Solving Rules 153
7.4.2.1 Goal Decomposition Rules 154
7.4.2.2 Iteration Rules 154
7.4.2.3 Contribution Rules 155
7.4.2.4 Cardinality Rules 155
7.4.3 Rule Combinations 155
7.5 Modeling Organizational Structure 156
7.5.1 GAIRE Model 156
7.6 Organizational Dynamics Analysis 159
7.7 Interaction Ontology 161
7.7.1 Interaction Protocols 161
7.7.2 Organizational Patterns 162
7.7.3 Interaction Levels 164
7.7.4 Interaction Rules 164
7.8 Interaction Protocols Engineering 164
7.8.1 Analysis 165
7.8.2 Interaction Protocol Ontology 165
7.8.3 Specifications of Interaction Protocol 167
7.8.4 Interaction Metaprotocols 168
7.9 Modeling Interaction Patterns 170
7.9.1 Pattern Description Template 170
7.9.2 Case Study: Contract Net Protocol 171
7.10 Agent-Environment Interaction 171
7.10.1 What is Agent-Environment Interaction? 171
7.10.2 Modeling Based on Markov Decision Process 174
7.10.3 Modeling Based on the Science of Complexity 176
7.10.4 Dynamic System Theory 178
7.10.5 Case Study: Markov State Chain 179
7.11 Summary 180
References 180
Chapter 8: Formal Modeling 183
8.1 Introduction 183
8.2 First-Order Linear-Time Temporal Logics 183
8.2.1 Formal Assertions 184
8.2.2 Real-Time Temporal Logics 185
8.3 Temporal Specification 186
8.4 Formulae for Organizational Abstraction 187
8.4.1 Actor 187
8.4.2 Environment 188
8.4.3 Rule 188
8.4.4 Properties and Keywords 189
8.5 Modeling Roles 191
8.6 Modeling Interaction 192
8.7 FIPA ACL Message Specifications 194
8.7.1 ACL Protocol Description Language 194
8.7.2 Modeling ACL Messages 195
8.8 Modeling Organizational Goal 196
8.9 Summary 198
References 198
Chapter 9: Integrative Modeling 199
9.1 Introduction 199
9.2 Integrating Functional and Nonfunctional Requirements 199
9.2.1 Functional Requirements Analysis 199
9.2.2 Nonfunctional Requirements Analysis 200
9.2.3 Analyzing Integrative Requirements 200
9.3 Visual Modeling 201
9.3.1 Goal-Oriented Visual Modeling 201
9.3.1.1 Strategic Dependency Model 202
9.3.1.2 Strategic Rationale Model 202
9.4 Formal Specifications 203
9.5 Integrative Modeling Framework 204
9.5.1 Business-Oriented Functional Requirements 204
9.5.2 Business-Oriented Nonfunctional Requirements 205
9.5.3 Integrative Modeling 205
9.6 Summary 206
References 207
Chapter 10: Agent Service-Oriented Architectural Design 209
10.1 Introduction 209
10.2 Agent Service Model 209
10.2.1 Agent Model 210
10.2.2 Service Model 211
10.3 Agent Service Design Patterns 212
10.3.1 Agent Architecture Patterns 212
10.3.1.1 Deductive Agent Architecture 212
10.3.1.2 Reactive Agent Architecture 214
10.3.1.3 Belief-Desire-Intention Agent Architecture 215
10.3.2 Structural and Functional Service Patterns 216
10.4 Agent Service-Oriented Integration Architectures 216
10.4.1 Integration Levels and Techniques 216
10.4.2 Architectures for Application Integration 219
10.5 Agent Service-Oriented Integration Strategies 221
10.5.1 Multiagent+Web Services 221
10.5.2 Multiagent+Service-Oriented Computing 223
10.6 Agent Service Management and Communications 224
10.7 Agent Service Coordination 225
10.7.1 Coordination Methods 225
10.7.1.1 Organizational Member-Level Coordination 226
10.7.1.2 Organization-Level Coordination 227
10.7.2 Coordination Modeling and Patterns 228
10.8 Case Study 231
10.9 Summary 232
References 232
Chapter 11: Agent Service-Oriented Detailed Design 234
11.1 Introduction 234
11.2 Agent Service Ontology 234
11.2.1 Extracting Problem-Solving Ontology 234
11.2.1.1 Associated Ontologies 235
11.2.1.2 Aggregated Ontologies 236
11.2.1.3 Generalized Hierarchical Ontologies 236
11.2.2 Developing Agent Service Ontology 236
11.3 Representation of Agent Services 237
11.3.1 Agent Service Specification 237
11.3.2 Case Study: Algorithm Registration Agent Service 239
11.4 Agent Service Endpoint Interfaces 240
11.4.1 Designing Agent Service Interfaces 240
11.4.2 Case Study: Algorithm Service Interface 242
11.5 Directory of Agent Services 244
11.6 Communication of Agent Services 247
11.7 Transport of Agent Services 247
11.8 Mediation of Agent Services 248
11.9 Discovery of Agent Services 249
11.10 Modeling Coordination 250
11.11 Other Strategic Issues 253
11.11.1 Design with Agent Service-Oriented Principles 253
11.11.2 Create a Custom Ontological Directory 253
11.11.3 Define a Schema Management Strategy 253
11.11.4 Always Relate XML to Data 254
11.12 Summary 254
References 254
Chapter 12: Ontological Engineering 256
12.1 Introduction 256
12.2 Ontology Profiles 257
12.2.1 From Ontology to Ontological Engineering 257
12.2.2 Domain-Specific Business Ontology 258
12.2.3 Problem-Solving Ontology 260
12.2.3.1 Business-Oriented Task Ontologies 262
12.2.3.2 Business Logic Ontologies 263
12.2.3.3 Resource Ontologies 264
12.2.4 Ontological Commitment 265
12.3 Ontological Semantic Relationships 267
12.4 Ontological Representation 269
12.4.1 Ontology Modeling Techniques 269
12.4.1.1 DL-Based Ontological Grammar 270
12.4.2 Representing Domain Ontologies 271
12.4.3 Representing Problem-Solving Ontologies 272
12.5 Ontological Semantic Aggregation and Transformation Cross Domains 274
12.5.1 Semantic Aggregation of Semantic Relationships 274
12.5.2 Semantic Aggregation of Ontological Items 275
12.5.3 Transformation Between Ontological Items 276
12.6 Summary 277
References 278
Chapter 13: OSOAD Case Study 280
13.1 Organization-Oriented System Analysis 280
13.2 Organizational Relationship Model 281
13.3 Organizational Rationale Model 284
13.4 Formal Analysis 286
13.5 Formal Refinement Using Scenario-Based Analysis 288
13.6 Agent Service-Driven Plug and Play 291
13.6.1 Plug and Play Modeling 291
13.6.2 Agent Service-Driven Plug and Play 292
13.6.2.1 Agent Service Description 292
13.6.2.2 Role Model for Plug and Play 293
13.6.2.3 Agent Service Specification 294
13.6.3 Implementation 294
13.7 M-Space for Macroeconomic Decision Support 295
13.8 Summary 298
References 299
Chapter 14: Actionable Knowledge Discovery and Delivery 300
14.1 Introduction 300
14.2 Issues with Existing KDD 301
14.3 Gap Analysis 303
14.3.1 Gaps Between Delivered and Desired 303
14.3.2 Aspects for Narrowing Gaps 305
14.4 An AKD Framework 306
14.4.1 AKD Problem Statement 307
14.4.2 Actionability Computing 309
14.4.3 AKD Concept Map 311
14.4.4 Ubiquitous Intelligence 311
14.4.4.1 Data Intelligence 312
14.4.4.2 Domain Intelligence 312
14.4.4.3 Human Intelligence 312
14.4.4.4 Network Intelligence 312
14.4.4.5 Social Intelligence 313
14.5 Deployment 313
14.5.1 Opportunities 313
14.5.2 AKD Architectures 315
14.5.3 AKD Implementation 315
14.5.3.1 Constrained Knowledge Delivery Environment 316
14.5.3.2 Cooperation Between Human and KDD Systems 316
14.5.3.3 Interactive and Parallel KDD Support 316
14.5.3.4 Closed-Loop and Iterative Refinement 316
14.5.3.5 Mining In-Depth Patterns 317
14.5.3.6 Post Mining 317
14.5.3.7 Combined Mining 317
14.5.3.8 Agent-Driven Actionable Knowledge Discovery 318
14.5.3.9 Knowledge Discovery as Service 318
14.5.4 Knowledge Delivery 318
14.6 An Example 319
14.7 Summary 321
References 322
Chapter 15: Learning Complex Behavioral and Social Data 326
15.1 Introduction 326
15.2 Complex Behavioral and Social Problems 327
15.2.1 Behavioral and Social System and Intelligence 327
15.2.2 Complexity of Behavioral and Social Systems 329
15.3 Non-IID Behavioral and Social Problems 330
15.3.1 Coupling 330
15.3.2 Heterogeneity 331
15.4 Issues in Classic Behavioral and Social Learning 333
15.4.1 Classic Behavior Analysis 333
15.4.2 Classic Social Media and Recommendation Systems 334
15.4.3 Classic Social Network Analysis 335
15.5 Non-IIDness Learning 336
15.6 Non-IIDness Learning Case Studies 338
15.6.1 Coupled Behavior Analysis 339
15.6.2 Coupled Item Recommendation 342
15.6.3 Term Coupling-Based Document Analysis 344
15.7 Summary 345
References 347
Chapter 16: Opportunities and Prospects 350
16.1 About Open Complex System Studies 350
16.2 About Metasynthetic Computing and Engineering 351
References 353
Index 355
| Erscheint lt. Verlag | 29.5.2015 |
|---|---|
| Reihe/Serie | Advanced Information and Knowledge Processing |
| Zusatzinfo | XIV, 348 p. 120 illus. |
| Verlagsort | London |
| Sprache | englisch |
| Themenwelt | Mathematik / Informatik ► Informatik ► Software Entwicklung |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Technik ► Elektrotechnik / Energietechnik | |
| Technik ► Maschinenbau | |
| Schlagworte | Agent-Based Computing • Complex Adaptive Systems • Complex Intelligent Information Systems • Large scale systems • Metasynthetic Computing • Open Complex Giant Systems • Organization-oriented Computing • service-oriented computing |
| ISBN-10 | 1-4471-6551-9 / 1447165519 |
| ISBN-13 | 978-1-4471-6551-4 / 9781447165514 |
| Haben Sie eine Frage zum Produkt? |
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