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Metasynthetic Computing and Engineering of Complex Systems 2015 ed. [Kõva köide]

  • Formaat: Hardback, 348 pages, kõrgus x laius: 235x155 mm, kaal: 6682 g, 120 Illustrations, black and white; XIV, 348 p. 120 illus., 1 Hardback
  • Sari: Advanced Information and Knowledge Processing
  • Ilmumisaeg: 10-Jun-2015
  • Kirjastus: Springer London Ltd
  • ISBN-10: 1447165500
  • ISBN-13: 9781447165507
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Metasynthetic Computing and Engineering of Complex Systems 2015 ed.Suurem pilt
  • Formaat: Hardback, 348 pages, kõrgus x laius: 235x155 mm, kaal: 6682 g, 120 Illustrations, black and white; XIV, 348 p. 120 illus., 1 Hardback
  • Sari: Advanced Information and Knowledge Processing
  • Ilmumisaeg: 10-Jun-2015
  • Kirjastus: Springer London Ltd
  • ISBN-10: 1447165500
  • ISBN-13: 9781447165507
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781447165507.html
Märksõnad:
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.
1 Complex Systems
1(36)
1.1 Introduction
1(1)
1.2 System Complexities
1(4)
1.3 System Transparency
5(2)
1.3.1 Black Boxes
5(1)
1.3.2 White Boxes
6(1)
1.3.3 Glass Boxes
6(1)
1.3.4 Grey Boxes
6(1)
1.4 System Classification
7(2)
1.5 Complex Agent Systems
9(10)
1.5.1 Multiagent Systems
9(4)
1.5.2 Large-Scale Systems
13(1)
1.5.3 Large-Scale Multiagent Systems
13(4)
1.5.4 Open Complex Agent Systems
17(2)
1.6 Hybrid Intelligent Systems
19(6)
1.6.1 Concept
19(1)
1.6.2 Hybridization Strategies
20(2)
1.6.3 Design Strategies
22(1)
1.6.4 Typical Hybrid Applications
23(2)
1.7 Evolution of Intelligent Systems
25(4)
1.8 Open Giant Intelligent Systems
29(2)
1.9 Computing and Engineering Complex Systems
31(2)
1.10 Summary
33(4)
References
33(4)
2 Ubiquitous Intelligence
37(14)
2.1 Introduction
37(1)
2.2 Data Intelligence
38(2)
2.2.1 What Is Data Intelligence?
38(1)
2.2.2 Aims of Involving Data Intelligence
38(1)
2.2.3 Aspects of Data Intelligence
39(1)
2.3 Domain Intelligence
40(1)
2.3.1 What Is Domain Intelligence?
40(1)
2.3.2 Aims of Involving Domain Intelligence
40(1)
2.3.3 Aspects of Domain Intelligence
41(1)
2.4 Network Intelligence
41(2)
2.4.1 What Is Network Intelligence?
41(1)
2.4.2 Aims of Involving Network Intelligence
42(1)
2.4.3 Aspects of Network Intelligence
42(1)
2.5 Human Intelligence
43(2)
2.5.1 What Is Human Intelligence?
43(1)
2.5.2 Aims of Involving Human Intelligence
43(1)
2.5.3 Aspects of Human Intelligence
44(1)
2.6 Organizational Intelligence
45(1)
2.6.1 What Is Organizational Intelligence?
45(1)
2.6.2 Aims of Involving Organizational Intelligence
45(1)
2.6.3 Aspects of Organizational Intelligence
46(1)
2.7 Social Intelligence
46(2)
2.7.1 What Is Social Intelligence?
46(1)
2.7.2 Aims of Involving Social Intelligence
47(1)
2.7.3 Aspects of Social Intelligence
47(1)
2.8 Metasynthesis of Ubiquitous Intelligence
48(1)
2.9 Summary
49(2)
References
49(2)
3 System Methodologies
51(6)
3.1 Introduction
51(1)
3.2 Reductionism
52(1)
3.3 Holism
53(1)
3.4 Systematology
53(2)
3.5 Summary
55(2)
References
55(2)
4 Computing Paradigms
57(24)
4.1 Introduction
57(1)
4.2 Objects and Object-Oriented Methodology
58(1)
4.3 Components and Component-Based Methodology
58(1)
4.4 Services and Service-Oriented Methodology
59(1)
4.5 Agents and Agent-Oriented Methodology
60(6)
4.5.1 Goal-Oriented Requirements Analysis
61(1)
4.5.2 Agent-Oriented Software Engineering
62(3)
4.5.3 Issues in Agent-Oriented Software Engineering
65(1)
4.6 Relations Among Agents, Objects, Components, and Services
66(1)
4.7 Autonomic Computing
67(3)
4.8 Organizational Computing
70(1)
4.9 Behavior Computing
71(3)
4.10 Social Computing
74(3)
4.11 Cloud/Service Computing
77(1)
4.12 Metasynthetic Computing
78(3)
References
78(3)
5 Metasynthesis
81(30)
5.1 Introduction
81(1)
5.2 Open Complex Giant Systems
81(4)
5.3 OCGS System Complexities
85(2)
5.4 Knowledge and Intelligence Emergence
87(6)
5.5 Theoretical Framework of Metasynthesis
93(2)
5.6 Problem-Solving Process in M-Space
95(3)
5.7 Social Cognitive Intelligence Emergence in M-Space
98(4)
5.7.1 Individual Cognitive Model
98(1)
5.7.2 Social Cognitive Interaction Model
99(2)
5.7.3 Cognitive Intelligence Emergence
101(1)
5.8 Thinking Pitfalls in M-Interactions
102(3)
5.9 M-Computing: Engineering OCGS
105(1)
5.10 Discussions
106(5)
References
108(3)
6 OSOAD Methodology
111(20)
6.1 Introduction
111(1)
6.2 Organizational Abstraction
111(5)
6.2.1 Actors
112(1)
6.2.2 Environment
113(1)
6.2.3 Interaction
113(1)
6.2.4 Organizational Rules
114(1)
6.2.5 Organizational Structure
114(1)
6.2.6 Organizational Goal
115(1)
6.2.7 Organizational Dynamics
115(1)
6.3 Organization-Oriented Analysis
116(3)
6.3.1 Challenges for Current Organization-Related Software Engineering
116(1)
6.3.2 What is Organization-Oriented Analysis?
117(2)
6.4 Agent Service-Oriented Design
119(5)
6.4.1 Agent Service, Services of Agent, and Services of Service
119(1)
6.4.2 Why Agent Service-Oriented Design?
119(1)
6.4.3 What is Agent Service-Oriented Design?
120(3)
6.4.4 Agent Service-Oriented Architectural Design
123(1)
6.4.5 Agent Service-Oriented Detailed Design
124(1)
6.5 Building Organization and Service-Oriented Software Engineering
124(3)
6.6 Summary
127(4)
References
127(4)
7 Visual Modeling
131(38)
7.1 Introduction
131(1)
7.2 Actor Model
131(4)
7.2.1 Actor Classification
131(2)
7.2.2 Role Model
133(2)
7.3 Environment Model
135(3)
7.3.1 Characteristics of Agent Environment
135(1)
7.3.2 Classification of Agent Environment
136(2)
7.3.3 POMDPAEI Model
138(1)
7.4 Modeling Organizational Rules
138(4)
7.4.1 Structural Rules
138(1)
7.4.2 Problem-Solving Rules
139(2)
7.4.3 Rule Combinations
141(1)
7.5 Modeling Organizational Structure
142(3)
7.5.1 GAIRE Model
142(3)
7.6 Organizational Dynamics Analysis
145(2)
7.7 Interaction Ontology
147(3)
7.7.1 Interaction Protocols
147(1)
7.7.2 Organizational Patterns
148(2)
7.7.3 Interaction Levels
150(1)
7.7.4 Interaction Rules
150(1)
7.8 Interaction Protocols Engineering
150(6)
7.8.1 Analysis
151(1)
7.8.2 Interaction Protocol Ontology
151(2)
7.8.3 Specifications of Interaction Protocol
153(1)
7.8.4 Interaction Metaprotocols
154(2)
7.9 Modeling Interaction Patterns
156(1)
7.9.1 Pattern Description Template
156(1)
7.9.2 Case Study: Contract Net Protocol
157(1)
7.10 Agent-Environment Interaction
157(9)
7.10.1 What is Agent-Environment Interaction?
157(3)
7.10.2 Modeling Based on Markov Decision Process
160(2)
7.10.3 Modeling Based on the Science of Complexity
162(2)
7.10.4 Dynamic System Theory
164(1)
7.10.5 Case Study: Markov State Chain
165(1)
7.11 Summary
166(3)
References
166(3)
8 Formal Modeling
169(16)
8.1 Introduction
169(1)
8.2 First-Order Linear-Time Temporal Logics
169(3)
8.2.1 Formal Assertions
170(1)
8.2.2 Real-Time Temporal Logics
171(1)
8.3 Temporal Specification
172(1)
8.4 Formulae for Organizational Abstraction
173(4)
8.4.1 Actor
173(1)
8.4.2 Environment
174(1)
8.4.3 Rule
174(1)
8.4.4 Properties and Keywords
175(2)
8.5 Modeling Roles
177(1)
8.6 Modeling Interaction
178(2)
8.7 FIPA ACL Message Specifications
180(2)
8.7.1 ACL Protocol Description Language
180(1)
8.7.2 Modeling ACL Messages
181(1)
8.8 Modeling Organizational Goal
182(2)
8.9 Summary
184(1)
References
184(1)
9 Integrative Modeling
185(10)
9.1 Introduction
185(1)
9.2 Integrating Functional and Nonfunctional Requirements
185(2)
9.2.1 Functional Requirements Analysis
185(1)
9.2.2 Nonfunctional Requirements Analysis
186(1)
9.2.3 Analyzing Integrative Requirements
186(1)
9.3 Visual Modeling
187(2)
9.3.1 Goal-Oriented Visual Modeling
187(2)
9.4 Formal Specifications
189(1)
9.5 Integrative Modeling Framework
190(2)
9.5.1 Business-Oriented Functional Requirements
190(1)
9.5.2 Business-Oriented Nonfunctional Requirements
191(1)
9.5.3 Integrative Modeling
191(1)
9.6 Summary
192(3)
References
193(2)
10 Agent Service-Oriented Architectural Design
195(26)
10.1 Introduction
195(1)
10.2 Agent Service Model
195(3)
10.2.1 Agent Model
196(1)
10.2.2 Service Model
197(1)
10.3 Agent Service Design Patterns
198(4)
10.3.1 Agent Architecture Patterns
198(4)
10.3.2 Structural and Functional Service Patterns
202(1)
10.4 Agent Service-Oriented Integration Architectures
202(5)
10.4.1 Integration Levels and Techniques
202(3)
10.4.2 Architectures for Application Integration
205(2)
10.5 Agent Service-Oriented Integration Strategies
207(3)
10.5.1 Multiagent + Web Services
207(2)
10.5.2 Multiagent + Service-Oriented Computing
209(1)
10.6 Agent Service Management and Communications
210(1)
10.7 Agent Service Coordination
211(6)
10.7.1 Coordination Methods
211(3)
10.7.2 Coordination Modeling and Patterns
214(3)
10.8 Case Study
217(1)
10.9 Summary
218(3)
References
218(3)
11 Agent Service-Oriented Detailed Design
221(22)
11.1 Introduction
221(1)
11.2 Agent Service Ontology
221(3)
11.2.1 Extracting Problem-Solving Ontology
221(2)
11.2.2 Developing Agent Service Ontology
223(1)
11.3 Representation of Agent Services
224(3)
11.3.1 Agent Service Specification
224(2)
11.3.2 Case Study: Algorithm Registration Agent Service
226(1)
11.4 Agent Service Endpoint Interfaces
227(4)
11.4.1 Designing Agent Service Interfaces
227(2)
11.4.2 Case Study: Algorithm Service Interface
229(2)
11.5 Directory of Agent Services
231(3)
11.6 Communication of Agent Services
234(1)
11.7 Transport of Agent Services
234(1)
11.8 Mediation of Agent Services
235(1)
11.9 Discovery of Agent Services
236(1)
11.10 Modeling Coordination
237(3)
11.11 Other Strategic Issues
240(1)
11.11.1 Design with Agent Service-Oriented Principles
240(1)
11.11.2 Create a Custom Ontological Directory
240(1)
11.11.3 Define a Schema Management Strategy
240(1)
11.11.4 Always Relate XML to Data
241(1)
11.12 Summary
241(2)
References
241(2)
12 Ontological Engineering
243(24)
12.1 Introduction
243(1)
12.2 Ontology Profiles
244(10)
12.2.1 From Ontology to Ontological Engineering
244(1)
12.2.2 Domain-Specific Business Ontology
245(2)
12.2.3 Problem-Solving Ontology
247(5)
12.2.4 Ontological Commitment
252(2)
12.3 Ontological Semantic Relationships
254(2)
12.4 Ontological Representation
256(5)
12.4.1 Ontology Modeling Techniques
256(2)
12.4.2 Representing Domain Ontologies
258(1)
12.4.3 Representing Problem-Solving Ontologies
259(2)
12.5 Ontological Semantic Aggregation and Transformation Cross Domains
261(3)
12.5.1 Semantic Aggregation of Semantic Relationships
261(1)
12.5.2 Semantic Aggregation of Ontological Items
262(1)
12.5.3 Transformation Between Ontological Items
263(1)
12.6 Summary
264(3)
References
265(2)
13 OSOAD Case Study
267(20)
13.1 Organization-Oriented System Analysis
267(1)
13.2 Organizational Relationship Model
268(3)
13.3 Organizational Rationale Model
271(2)
13.4 Formal Analysis
273(2)
13.5 Formal Refinement Using Scenario-Based Analysis
275(3)
13.6 Agent Service-Driven Plug and Play
278(4)
13.6.1 Plug and Play Modeling
278(1)
13.6.2 Agent Service-Driven Plug and Play
279(2)
13.6.3 Implementation
281(1)
13.7 M-Space for Macroeconomic Decision Support
282(3)
13.8 Summary
285(2)
References
286(1)
14 Actionable Knowledge Discovery and Delivery
287(26)
14.1 Introduction
287(1)
14.2 Issues with Existing KDD
288(2)
14.3 Gap Analysis
290(3)
14.3.1 Gaps Between Delivered and Desired
290(2)
14.3.2 Aspects for Narrowing Gaps
292(1)
14.4 An AKD Framework
293(7)
14.4.1 AKD Problem Statement
294(2)
14.4.2 Actionability Computing
296(2)
14.4.3 AKD Concept Map
298(1)
14.4.4 Ubiquitous Intelligence
298(2)
14.5 Deployment
300(6)
14.5.1 Opportunities
300(2)
14.5.2 AKD Architectures
302(1)
14.5.3 AKD Implementation
302(3)
14.5.4 Knowledge Delivery
305(1)
14.6 An Example
306(2)
14.7 Summary
308(5)
References
309(4)
15 Learning Complex Behavioral and Social Data
313(24)
15.1 Introduction
313(1)
15.2 Complex Behavioral and Social Problems
314(3)
15.2.1 Behavioral and Social System and Intelligence
314(2)
15.2.2 Complexity of Behavioral and Social Systems
316(1)
15.3 Non-IID Behavioral and Social Problems
317(3)
15.3.1 Coupling
317(1)
15.3.2 Heterogeneity
318(2)
15.4 Issues in Classic Behavioral and Social Learning
320(3)
15.4.1 Classic Behavior Analysis
320(1)
15.4.2 Classic Social Media and Recommendation Systems
321(1)
15.4.3 Classic Social Network Analysis
322(1)
15.5 Non-IIDness Learning
323(2)
15.6 Non-IIDness Learning Case Studies
325(7)
15.6.1 Coupled Behavior Analysis
326(3)
15.6.2 Coupled Item Recommendation
329(2)
15.6.3 Term Coupling-Based Document Analysis
331(1)
15.7 Summary
332(5)
References
334(3)
16 Opportunities and Prospects
337(6)
16.1 About Open Complex System Studies
337(1)
16.2 About Metasynthetic Computing and Engineering
338(5)
References
340(3)
Index 343