Systems science: theory, analysis, modeling, and design
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[2022]
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| Beschreibung: | xxi, 814 Seiten Illustrationen, Diagramme |
| ISBN: | 9783030934811 |
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Datensatz im Suchindex
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| adam_text | Contents 1 Introduction............................................................................................ 1.1 What This Book Is About................................................................ 1.1.1 Talking About Systems....................................................... 1.1.2 The Nature of Systems Science........................................... 1.1.3 Concrete and Abstract Systems........................................... 1.1.4 Systems and Complexity..................................................... 1.1.5 Deep Understanding............................................................. 1.1.6 Understanding Systems....................................................... 1.1.7 Understanding Causal Relations......................................... 1.1.8 New Kinds of Causal Relations........................................... 1.1.9 Complexity and Interactions............................................... 1.1.10 Simple to Complex Adaptive and Evolvable Systems......... 1.2 A Systems Understanding Framework........................................... 1.2.1 Conventional Systems Understanding................................. 1.2.2 Outline of the Framework................................................... 1.3 Sharing Understanding..................................................................... 1.3.1 Communications................................................................. 1.3.2 The Language of Systems................................................... 1.3.3 The Story of S: System Narratives....................................... 1.3.4 The
Mathematics of Systems............................................... 1.3.5 Discrete Mathematics........................................................... 1.4 Deep Systems Analysis (DSA)....................................................... 1.4.1 System Identification: Boundary Determination................. 1.4.2 Environment Analysis: Sources, Sinks, and Disturbances.. 1.4.3 Recursive System Decomposition....................................... 1.5 The System Knowledgebase........................................................... 1.6 Synopsis and Motivation................................................................. 1 1 5 6 8 10 14 15 17 17 18 19 20 21 22 23 24 25 27 28 28 29 31 32 33 34 34
Part I 2 Foundations of Systems Understanding Principles of Systems Science................................................... .............. 2.1 2.2 2.3 2.4 2.5 The Systems Approach.................................................................. 2.1.1 Systems Intuitions, Thinking, and Sensibility.................... 2.1.2 Examples of the Systems Approach Within Disciplines ... 2.1.3 Possible Issues with Current Practices................................ 2.1.4 A Principled Systems Approach........................................ The Concept of a System................................................................ 2.2.1 Definition........................................................................... 2.2.2 Systems That Seem Ephemeral.......................................... 2.2.3 Systems Equivalencies....................................................... Principles of Systems Science Reviewed........................................ 2.3.1 Principle 1: Sy sternness (M K Chapter 1)........................ 2.3.2 Principle 2: Systems Are Processes Organized in Structural and Functional Hierarchies (M K Chapter 3)................................................................ 2.3.3 Principle 3 : Systems Are Networks of Relations Among Components and Can Be Represented Abstractly as Such Networks of Relations (M K Chapter 4)............ 2.3.4 Principle 4: Systems Are Dynamic over Multiple Spatial and Time Scales (M K Chapter 6)............ 63 2.3.5 Principle 5: Systems Exhibit Various Kinds and Levels of Complexity (M K Chapter 5).......... 63 2.3.6 Principle 6: Systems
Evolve (M K Chapters 10 and 11).................................... 64 2.3.7 Principle 7: Systems Encode Knowledge and Receive and Send Information (M K Chapters 7 and 8).... 65 2.3.8 Principle 8: Systems Have Regulatory Subsystems to Achieve Stability (M K Chapter 9).................. 65 2.3.9 Principle 9: Systems Can Contain Models of Other Systems (M K Chapters 8 and 13)........................ 66 2.3.10 Principle 10: Sufficiently Complex, Adaptive Systems Can Contain Models of Themselves (M K Chapters 7, 8, 9 and 13)...................................................... 2.3.11 Principle 11: Systems Can Be Understood (a Corollary of #9, M K Chapters 12 and 13).................. 2.3.12 Principle 12: Systems Can Be Improved (a Corollary of #6, Chapter 12).............................. Systems Science.............................................................................. 2.4.1 “Problems” to Be Solved................................................... 2.4.2 Systems Science as a Meta-Science................................... What Goes Wrong.......................................................................... 2.5.1 The Software Development Process................................. 2.5.2 Systems Engineering Process........................................... 2.5.3 The Sciences..................................................................... 41 41 44 45 47 48 49 50 52 55 56 59 60 61 66 67 68 69 70 75 80 81 85 86
What Could GoRight.................................................................... Proceeding withPrincipled Methods.............................................. 86 87 System Ontology......................................................................................... 3.1 What Exists................................................................................... 89 90 92 93 93 94 96 116 125 126 141 144 144 146 157 159 160 160 160 160 162 172 172 174 175 2.6 2.7 3 3.2 3.3 3.4 3.5 3.6 3.7 4 3.1.1 Categories and Type Hierarchies....................................... 3.1.2 Recurring Patterns at All Scales......................................... 3.1.3 Origins of Things: A Universal Process............................. What Is “a” System Ontology, and Why Does It Matter?.............. 3.2.1 System Philosophy............................................................. 3.2.2 Examples of Developing a System Ontology................... Ontogenesis: The Origin and Development of Systems................ 3.3.1 The Ontogenie Cycle......................................................... 3.3.2 Other Takes on Ontogenesis............................................. An Ontological Framework............................................................ 3.4.1 The Framework, Its Purpose, and Its Justifications........... 3.4.2 The Aspects....................................................................... 3.4.3 Using the Framework......................................................... 3.4.4 Upper Ontology................................................................. 3.4.5
System Domain Ontology................................................. 3.4.6 Discipline Domain Ontologies........................................... The System Ontology.................................................................... 3.5.1 Background Categories..................................................... 3.5.2 Framework Elements......................................................... Putting It All Together.................................................................... 3.6.1 Terminology....................................................................... 3.6.2 Accounting for Everything............................................... Summary of Ontology and Ontogeny............................................ A Model of System and a Language to Represent It............................ 4.1 In This Chapter................................................................................ 4.2 The Communication of Ideas.......................................................... 4.2.1 Representations of Concepts, Beliefs, and Ideas................ 4.2.2 Names of Things—Abstraction and Language.................. 4.2.3 Language of Thought and Innate Concepts........................ 4.2.4 The Systemese Hypothesis................................................ 4.3 A Formal Definition of System..................................................... 4.3.1 Verbal.................................................................................. 4.3.2 Graphical............................................................................ 4.3.3 A Mathematical Structure
Defining a System.................... 4.4 Toward a Language of Systems..................................................... 4.4.1 Semantics............................................................................ 4.5 Example......................................................................................... 4.6 Conclusion..................................................................................... 177 177 179 180 183 183 185 188 189 190 190 211 212 214 224
5 An Introduction to the Process of Understanding Systems................. 227 From General Systems Principles and Theories to Actual Systems Knowledge............................................... 227 5.1.1 From Observing to Characterizing to Modeling................ 5.1.2 All Sustainable Processes Are Systems.............................. 5.1.3 A Generalized Process Applied to Any Domain................ 5.2 The System for Understanding Complex Systems.......................... 5.2.1 The General Flow Through................................................ 5.2.2 Component 1: Deep Analysis............................................... 5.2.3 Component 2: The Knowledgebase..................................... 5.2.4 Component 3: Modeling..................................................... 5.2.5 Component 4: Simulations and Hypotheses Testing........... 5.2.6 Components: Generating Designs or Policies................... 5.2.7 Component 6: Monitoring Behaviors................................. 5.2.8 Component 7: Process Governance.................................... 5.3 Cost-Benefit of the Process............................................................ 5.4 Conclusion....................................................................................... 228 230 231 231 232 233 239 240 241 241 242 243 243 246 5.1 Part II Analysis for Understanding 6 The Process of Deep Systems Analysis................................................... 6.1 What We Seek to Achieve.............................................................. 6.2 Perspectives on Systems
Analysis.................................................. 6.2.1 Kiir’s General Systems Problem Solver............................ 6.2.2 Checkland’s Soft Systems Methodology............................ 6.2.3 Synthesis............................................................................ 6.3 Obtaining Knowledge of the General Systems.............................. 6.3.1 Formal Procedures.............................................................. 6.3.2 Representations of the System............................................ 6.3.3 A Preview of the Most Complex Systems of Interest........ 6.4 “Deep” Analysis.............................................................................. 6.4.1 Inhibitors............................................................................ 6.4.2 The Objective: Reductionism with Maintenance of Relations................................................................ 265 6.4.3 The Three Phases of Systems Analysis............................. 6.5 System (of Interest) Identification.................................................. 6.5.1 Initialization........................................................................ 6.5.2 Proceed Around the Boundary........................................... 6.5.3 Estimate the System Transformation Function................. 6.6 Environmental Analysis.................................................................. 6.6.1 Limited Models of Entities and Influence Sources........... 6.6.2 Identifying the Sources and Sinks...................................... 6.7 Deconstructing the
System............................................................ 6.7.1 From an Opaque Object to a Transparent System............. 6.7.2 Finding Subsystems............................................................ 6.7.3 Recursive Decomposition.................................................. 6.7.4 Reverse Decomposition..................................................... 249 249 251 251 253 254 255 255 256 257 261 263 265 270 271 284 288 288 288 290 293 294 294 304 307
7 6.8 6.9 Iterative Analysis................................................................................ Considering Advanced Concepts....................................................... 6.9.1 Dealing with Fuzzy Systems................................................. 6.9.2 Dealing with Adaptivity.......................................................... 6.9.3 Dealing with Evolvability..................................................... 6.9.4 Dealing with Memory—And the Я Object.......................... 6.10 Conclusion........................................................................................... 311 311 312 314 317 318 320 Analyzing Various Kinds of Example Systems........................................ 323 Analysis of Example Complex, Complex Adaptive, and Complex Adaptive and Evolvable Systems...................... 323 7.2 The Digital Computing System.......................................................... 7.2.1 A Simple Computer........ ...................................................... 7.2.2 Decomposition....................................................................... 7.2.3 Environment and SOI Identification................................... 7.2.4 Knowledge and Generating Models...................................... 7.2.5 Transitioning the Complexity Boundary............................. 7.3 The Biological Neuron—A Complex, Adaptive System................. 7.3.1 Identification of the SOI—The “Typical” Neuron................ 7.3.2 Analysis of the Boundary and Environment........................ 7.3.3 Internal
Decomposition........................................................... 7.4 The Brain—A Complex, Adaptive, and Evolvable System............. 7.4.1 Brain Science.......................... 7.4.2 Brain Complexity..................................................................... 7.4.3 Overall Organization—Mammalian Brain............................. 7.4.4 Levels 1 and 0 (Preliminary Look)....................................... 7.4.5 The Brain Structural Decomposition Tree............................. 7.4.6 Behavior.................................................................................... 7.5 The Organization System.................................................................... 7.6 The Human Social System (HSS)..................................................... 7.6.1 Looking Down from the International Space Station—A Brief Examination of the Earth Supra-System.......................................................................... 7.6.2 The View from a U2 Spy Plane—The HSS.......................... 7.6.3 The Human Social System in the Earth Supra-System .... 7.7 Summation............................................................................................ 7.1 8 8.2 8.3 351 353 353 358 359 Why We Call It a Systems Knowledgebase...................................... 359 8.1.1 The Ontological Status of Knowledge................................... 360 8.1.2 Knowledge Accumulation...................................................... 362 8.1.3 Knowledge Use....................................................................... 367 8.1.4 The
Knowledgebase Structure Fulfills These Needs........... 368 Capture and Storage of the Relevant Aspects of a System............. 372 8.2.1 A Relational Database Schema for theKnowledgebase ... 374 Details of Relations/Tables................................................................ 381 Capturing Knowledge of the System.......................................................... 8.1 326 327 328 328 333 333 334 335 335 336 340 341 343 344 345 345 347 347 349
8.4 8.5 9 8.3.1 System Table...................................................................... 381 8.3.2 Components Table............................................. 385 Generating Dynamic Models........................................ ................ 387 Conclusion..................................................................................... 389 The Human Social System Economy as Subsystem: A Preliminary Analysis.................................................................. 391 9.1 Purpose of the Chapter................................................................... 9.2 Analytic Approaches..................................................................... 9.2.1 From the Current Subsystem As We Find It...................... 9.2.2 From the Historical Evolution of the Subsystem................ 9.2.3 From the Ideal of a CAES.................................................. 9.3 The HSS Decomposed................................................................... 9.3.1 The Fuzziness of Systems.................................................. 9.3.2 Defuzzification of the HSS................................................ 9.4 Deep Systems Analysis Applied to the Economic System............ 9.4.1 Analysis of the Environment.............................................. 9.4.2 Approximation of the System Function (See Sect. 6.5.3)...................................................... 420 9.5 Identification of the Economic Subsystem.................................... 9.5.1 Resolving the Boundary of the Economy as a
Subsystem........................................................ 421 9.5.2 The Historical Perspective................................................... 9.5.3 A Modern Perspective......................................................... 9.6 The Energy Sector and Biophysical Economic Factors.................. 9.6.1 Basics of Thermodynamics, Energy Flows, Work, and the Production of Wealth.................................. 9.6.2 Energy Capture, Conversion, and Delivery to Consumers...................................................................... 9.6.3 Energy Consumption: Work Processes, Efficiencies, and Waste...................................................... 9.7 Systemic Dysfunctions................................................................... 9.7.1 Values and Value Signaling................................................. 9.7.2 Emphasis on Growth........................................................... 9.7.3 Neoliberal Capitalism......................................................... 9.8 Conclusion..................................................................................... 391 396 396 397 398 398 401 402 415 416 421 422 428 440 441 457 461 462 463 464 465 465 Part III Archetype Models: Complex, Adaptive, and Evolvable Systems 10 Model Archetypes for CAS, CAES...................................................... 10.1 Models of Complex Systems and Model Archetypes.................. 10.1.1 Representing Models........................................................ 10.1.2 Systems Dynamics Models—Simulations........................ 10.1.3 A General
Systems Model................................................ 10.2 What Are Model Archetypes?...................................................... 469 469 472 472 473 473
10.2.1 The General CAS/CAES Architecture.............................. 10.2.2 Archetype Models Overview............................................ 10.3 Complex Adaptive and Evolvable Systems—The Archetype Model.................................................................................. 481 10.3.1 Complexity........................................................................ 10.3.2 CAS.................................................................................. 10.3.3 CAES................................................................................ 10.4 The CAS/CAES Framework and Prior Models............................. 10.4.1 Viable Systems Theory/Model.......................................... 10.4.2 Living Systems Theory—James Grier Miller.................. 10.4.3 Synthesis and Incorporating Other Work.......................... 10.5 Expanding the CAS/CAES........................................................... 475 478 485 486 492 496 497 502 504 508 11 The Agent Model.................................................................................... 11.1 Purpose of This Chapter................................................................. 11.2 Agents........................................................................................... 11.2.1 The Basic Agent System.................................................. 11.2.2 Decision-Making.............................................................. 11.2.3 Autonomy....................................................................... 11.2.4 Ideal
Agents..................................................................... 11.2.5 Agent Roles and Decision Types...................................... 11.3 Complex Environments................................................................. 11.3.1 Uncertainty in Interactions................................................ 11.3.2 Information Theoretical Considerations.......................... 11.3.3 Computational Engine...................................................... 11.3.4 Decision Model................................................................ 11.4 Agency........................................................................................... 11.4.1 Affective and Effective Action and the Subsequent State of the Environment.................................... 538 11.4.2 Feedback Through the Environment and the Causal Loop............................................ 540 11.5 Complexity and Autonomy........................................................... 11.6 Conclusion..................................................................................... 509 509 509 510 513 519 525 526 527 527 530 531 531 538 12 The Governance Model........................................................................ 12.1 Purpose of This Chapter................................................................ 12.2 The Concept of Governance......................................................... 12.2.1 The Purpose of Governance............................................. 12.2.2 Definitions....................................................................... 12.2.3
Decision Agents in Governance Systems......................... 12.3 Hierarchical Cybernetic Governance System (HCGS)................. 12.3.1 Energy Requirements Per Level....................................... 12.3.2 Administration of Work Processes: Classical Cybernetics........................................................ 12.3.3 Operations-Level Networks: Cooperation........................ 12.3.4 Coordination-Level Decision Managers......................... 547 547 554 554 557 564 568 569 541 544 570 573 584
12.3.5 Strategie.......................................................... 12.3.6 Comparing Stafford Beer’s VSM with the CAS/CAES Governance Architecture.................................... 610 12.4 Examples of the HCGS in Nature................................................ 12.4.1 Regulating Cellular Metabolism..................................... 12.4.2 Regulating Multicellular Physiology............................... 12.4.3 The Human Brain as an HCGS........................................ 12.5 The HCGS and Governance of the Human Social Systems........ 12.5.1 Typical Government Architectures and the HCGS Model........................................................ 12.5.2 The HSS as a CAES......................................................... 12.6 Conclusion................................................................................... 13 599 611 611 612 614 618 620 623 623 The Economy Model.............................................................................. 625 13.1 What Is an Economy?................................................................. 625 13.1.1 What Is Not in an Economy............................................. 629 13.1.2 What Then Is an Economy?............................................. 634 13.2 Considering a Generic Economic System.................................... 635 13.2.1 Common Attributes of an Economy............................... 635 13.2.2 Economy as a Value-Adding Supply Chain..................... 641 13.2.3 Market Dynamics............................................................. 644 13.2.4 Governance
Processes..................................................... 649 13.2.5 Extraction of Resources................................................... 653 13.2.6 Production of Useful Goods and Services....................... 657 13.2.7 Distribution—Moving Atoms, Energies,and Bits............ 660 13.2.8 Consumption................................................................... 661 13.2.9 Exporting Products and Wastes....................................... 661 13.2.10 A Note on Disturbances................................................... 662 13.3 Nested Economies....................................................................... 662 13.3.1 Metabolism..................................................................... 663 13.3.2 Physiology in Multicellular Organisms........................... 667 13.3.3 Family Economics........................................................... 671 13.4 The Economics of a CAS/CAES.................................................. 671 13.4.1 Generic Economic Archetype......................................... 671 13.4.2 Comparisons: Natural Versus Human Economies........... 676 13.4.3 Competition and Cooperation......................................... 681 13.5 Conclusion.................................................................................... 682 Part IV Designing CAES Artifactual Systems 14 Complex Artifactual Systems................................................................ 14.1 The Purpose of This Chapter........................................................ 14.1.1 What Is an
Artifact?.......................................................... 14.1.2 Artifact/Cultural Evolution.............................................. 14.1.3 The Artifact Creation (or Improvement) Process.............. 14.1.4 The Artifact Cycle............................................................ 687 687 691 692 695 696
14.2 CAS/CAES Artifacts....................................................... 14.2.1 Design and Engineering for Increasingly Complex Artifacts.............................................................. 701 14.2.2 Design Considerations..................................................... 14.2.3 Design for Emergence..................................................... 14.3 Intentional Ontogenesis and Evolution....................................... 14.3.1 Solving Problems, Expanding Capabilities...................... 14.3.2 Incremental Improvement as Evolution............................ 14.3.3 Admitting Evolution into the Design and Engineering Process.................................... 721 14.4 Conclusion.................................................................................... 700 712 714 715 716 721 722 15 Designing Complex, Adaptive, and Evolvable Systems........................ 725 15.1 The Purpose of This Chapter........................................................ 725 15.2 Process of System Design and Engineering.................................. 729 15.2.1 How Do We Design Complex Systems?.......................... 15.2.2 CAES Archetype As Template.......................................... 15.3 Designing the Food-Producing Module........................................ 15.3.1 The Agri-Village............................................................. 15.3.2 Purposes............................................................................ 15.3.3 Environment—Level-1 .................................................... 15.3.4 Input/Output—-Level
0...................................................... 15.3.5 Internal Processes—Leveli.............................................. 15.3.6 Discussion........................................................................ 15.4 Conclusion.................................................................................... 16 729 734 743 745 746 748 752 754 757 758 759 759 16.2 Systems Design for the Human Social System............................. 762 16.2.1 Considering the Current Realization of CAES Subsystems........................................................ 763 16.2.2 An Architectural Design for the HSS................................ 773 16.3 Designing a Human Social System as a Complex Adaptive and Evolvable System........................................ 776 16.3.1 Designing for Faulty Agents........................................... 777 16.3.2 Designing a Sustainable Economy.................................... 779 16.3.3 Social Organization......................................................... 790 16.3.4 Governance..................................................................... 794 16.4 Conclusion.................................................................................... 803 Societal Systems......................................................................................... 16.1 Purpose of This Chapter................................................................ Bibliography........................................................................................................ 805
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Contents 1 Introduction. 1.1 What This Book Is About. 1.1.1 Talking About Systems. 1.1.2 The Nature of Systems Science. 1.1.3 Concrete and Abstract Systems. 1.1.4 Systems and Complexity. 1.1.5 Deep Understanding. 1.1.6 Understanding Systems. 1.1.7 Understanding Causal Relations. 1.1.8 New Kinds of Causal Relations. 1.1.9 Complexity and Interactions. 1.1.10 Simple to Complex Adaptive and Evolvable Systems. 1.2 A Systems Understanding Framework. 1.2.1 Conventional Systems Understanding. 1.2.2 Outline of the Framework. 1.3 Sharing Understanding. 1.3.1 Communications. 1.3.2 The Language of Systems. 1.3.3 The Story of S: System Narratives. 1.3.4 The
Mathematics of Systems. 1.3.5 Discrete Mathematics. 1.4 Deep Systems Analysis (DSA). 1.4.1 System Identification: Boundary Determination. 1.4.2 Environment Analysis: Sources, Sinks, and Disturbances. 1.4.3 Recursive System Decomposition. 1.5 The System Knowledgebase. 1.6 Synopsis and Motivation. 1 1 5 6 8 10 14 15 17 17 18 19 20 21 22 23 24 25 27 28 28 29 31 32 33 34 34
Part I 2 Foundations of Systems Understanding Principles of Systems Science. . 2.1 2.2 2.3 2.4 2.5 The Systems Approach. 2.1.1 Systems Intuitions, Thinking, and Sensibility. 2.1.2 Examples of the Systems Approach Within Disciplines . 2.1.3 Possible Issues with Current Practices. 2.1.4 A Principled Systems Approach. The Concept of a System. 2.2.1 Definition. 2.2.2 Systems That Seem Ephemeral. 2.2.3 Systems Equivalencies. Principles of Systems Science Reviewed. 2.3.1 Principle 1: Sy sternness (M K Chapter 1). 2.3.2 Principle 2: Systems Are Processes Organized in Structural and Functional Hierarchies (M K Chapter 3). 2.3.3 Principle 3 : Systems Are Networks of Relations Among Components and Can Be Represented Abstractly as Such Networks of Relations (M K Chapter 4). 2.3.4 Principle 4: Systems Are Dynamic over Multiple Spatial and Time Scales (M K Chapter 6). 63 2.3.5 Principle 5: Systems Exhibit Various Kinds and Levels of Complexity (M K Chapter 5). 63 2.3.6 Principle 6: Systems
Evolve (M K Chapters 10 and 11). 64 2.3.7 Principle 7: Systems Encode Knowledge and Receive and Send Information (M K Chapters 7 and 8). 65 2.3.8 Principle 8: Systems Have Regulatory Subsystems to Achieve Stability (M K Chapter 9). 65 2.3.9 Principle 9: Systems Can Contain Models of Other Systems (M K Chapters 8 and 13). 66 2.3.10 Principle 10: Sufficiently Complex, Adaptive Systems Can Contain Models of Themselves (M K Chapters 7, 8, 9 and 13). 2.3.11 Principle 11: Systems Can Be Understood (a Corollary of #9, M K Chapters 12 and 13). 2.3.12 Principle 12: Systems Can Be Improved (a Corollary of #6, Chapter 12). Systems Science. 2.4.1 “Problems” to Be Solved. 2.4.2 Systems Science as a Meta-Science. What Goes Wrong. 2.5.1 The Software Development Process. 2.5.2 Systems Engineering Process. 2.5.3 The Sciences. 41 41 44 45 47 48 49 50 52 55 56 59 60 61 66 67 68 69 70 75 80 81 85 86
What Could GoRight. Proceeding withPrincipled Methods. 86 87 System Ontology. 3.1 What Exists. 89 90 92 93 93 94 96 116 125 126 141 144 144 146 157 159 160 160 160 160 162 172 172 174 175 2.6 2.7 3 3.2 3.3 3.4 3.5 3.6 3.7 4 3.1.1 Categories and Type Hierarchies. 3.1.2 Recurring Patterns at All Scales. 3.1.3 Origins of Things: A Universal Process. What Is “a” System Ontology, and Why Does It Matter?. 3.2.1 System Philosophy. 3.2.2 Examples of Developing a System Ontology. Ontogenesis: The Origin and Development of Systems. 3.3.1 The Ontogenie Cycle. 3.3.2 Other Takes on Ontogenesis. An Ontological Framework. 3.4.1 The Framework, Its Purpose, and Its Justifications. 3.4.2 The Aspects. 3.4.3 Using the Framework. 3.4.4 Upper Ontology. 3.4.5
System Domain Ontology. 3.4.6 Discipline Domain Ontologies. The System Ontology. 3.5.1 Background Categories. 3.5.2 Framework Elements. Putting It All Together. 3.6.1 Terminology. 3.6.2 Accounting for Everything. Summary of Ontology and Ontogeny. A Model of System and a Language to Represent It. 4.1 In This Chapter. 4.2 The Communication of Ideas. 4.2.1 Representations of Concepts, Beliefs, and Ideas. 4.2.2 Names of Things—Abstraction and Language. 4.2.3 Language of Thought and Innate Concepts. 4.2.4 The Systemese Hypothesis. 4.3 A Formal Definition of System. 4.3.1 Verbal. 4.3.2 Graphical. 4.3.3 A Mathematical Structure
Defining a System. 4.4 Toward a Language of Systems. 4.4.1 Semantics. 4.5 Example. 4.6 Conclusion. 177 177 179 180 183 183 185 188 189 190 190 211 212 214 224
5 An Introduction to the Process of Understanding Systems. 227 From General Systems Principles and Theories ' to Actual Systems Knowledge. 227 5.1.1 From Observing to Characterizing to Modeling. 5.1.2 All Sustainable Processes Are Systems. 5.1.3 A Generalized Process Applied to Any Domain. 5.2 The System for Understanding Complex Systems. 5.2.1 The General Flow Through. 5.2.2 Component 1: Deep Analysis. 5.2.3 Component 2: The Knowledgebase. 5.2.4 Component 3: Modeling. 5.2.5 Component 4: Simulations and Hypotheses Testing. 5.2.6 Components: Generating Designs or Policies. 5.2.7 Component 6: Monitoring Behaviors. 5.2.8 Component 7: Process Governance. 5.3 Cost-Benefit of the Process. 5.4 Conclusion. 228 230 231 231 232 233 239 240 241 241 242 243 243 246 5.1 Part II Analysis for Understanding 6 The Process of Deep Systems Analysis. 6.1 What We Seek to Achieve. 6.2 Perspectives on Systems
Analysis. 6.2.1 Kiir’s General Systems Problem Solver. 6.2.2 Checkland’s Soft Systems Methodology. 6.2.3 Synthesis. 6.3 Obtaining Knowledge of the General Systems. 6.3.1 Formal Procedures. 6.3.2 Representations of the System. 6.3.3 A Preview of the Most Complex Systems of Interest. 6.4 “Deep” Analysis. 6.4.1 Inhibitors. 6.4.2 The Objective: Reductionism with Maintenance of Relations. 265 6.4.3 The Three Phases of Systems Analysis. 6.5 System (of Interest) Identification. 6.5.1 Initialization. 6.5.2 Proceed Around the Boundary. 6.5.3 Estimate the System Transformation Function. 6.6 Environmental Analysis. 6.6.1 Limited Models of Entities and Influence Sources. 6.6.2 Identifying the Sources and Sinks. 6.7 Deconstructing the
System. 6.7.1 From an Opaque Object to a Transparent System. 6.7.2 Finding Subsystems. 6.7.3 Recursive Decomposition. 6.7.4 Reverse Decomposition. 249 249 251 251 253 254 255 255 256 257 261 263 265 270 271 284 288 288 288 290 293 294 294 304 307
7 6.8 6.9 Iterative Analysis. Considering Advanced Concepts. 6.9.1 Dealing with Fuzzy Systems. 6.9.2 Dealing with Adaptivity. 6.9.3 Dealing with Evolvability. 6.9.4 Dealing with Memory—And the Я Object. 6.10 Conclusion. 311 311 312 314 317 318 320 Analyzing Various Kinds of Example Systems. 323 Analysis of Example Complex, Complex Adaptive, and Complex Adaptive and Evolvable Systems. 323 7.2 The Digital Computing System. 7.2.1 A Simple Computer. . 7.2.2 Decomposition. 7.2.3 Environment and SOI Identification. 7.2.4 Knowledge and Generating Models. 7.2.5 Transitioning the Complexity Boundary. 7.3 The Biological Neuron—A Complex, Adaptive System. 7.3.1 Identification of the SOI—The “Typical” Neuron. 7.3.2 Analysis of the Boundary and Environment. 7.3.3 Internal
Decomposition. 7.4 The Brain—A Complex, Adaptive, and Evolvable System. 7.4.1 Brain Science. 7.4.2 Brain Complexity. 7.4.3 Overall Organization—Mammalian Brain. 7.4.4 Levels 1 and 0 (Preliminary Look). 7.4.5 The Brain Structural Decomposition Tree. 7.4.6 Behavior. 7.5 The Organization System. 7.6 The Human Social System (HSS). 7.6.1 Looking Down from the International Space Station—A Brief Examination of the Earth Supra-System. 7.6.2 The View from a U2 Spy Plane—The HSS. 7.6.3 The Human Social System in the Earth Supra-System . 7.7 Summation. 7.1 8 8.2 8.3 351 353 353 358 359 Why We Call It a Systems Knowledgebase. 359 8.1.1 The Ontological Status of Knowledge. 360 8.1.2 Knowledge Accumulation. 362 8.1.3 Knowledge Use. 367 8.1.4 The
Knowledgebase Structure Fulfills These Needs. 368 Capture and Storage of the Relevant Aspects of a System. 372 8.2.1 A Relational Database Schema for theKnowledgebase . 374 Details of Relations/Tables. 381 Capturing Knowledge of the System. 8.1 326 327 328 328 333 333 334 335 335 336 340 341 343 344 345 345 347 347 349
8.4 8.5 9 8.3.1 System Table. 381 8.3.2 Components Table. 385 Generating Dynamic Models. \. 387 Conclusion. 389 The Human Social System Economy as Subsystem: A Preliminary Analysis. 391 9.1 Purpose of the Chapter. 9.2 Analytic Approaches. 9.2.1 From the Current Subsystem As We Find It. 9.2.2 From the Historical Evolution of the Subsystem. 9.2.3 From the Ideal of a CAES. 9.3 The HSS Decomposed. 9.3.1 The Fuzziness of Systems. 9.3.2 Defuzzification of the HSS. 9.4 Deep Systems Analysis Applied to the Economic System. 9.4.1 Analysis of the Environment. 9.4.2 Approximation of the System Function (See Sect. 6.5.3). 420 9.5 Identification of the Economic Subsystem. 9.5.1 Resolving the Boundary of the Economy as a
Subsystem. 421 9.5.2 The Historical Perspective. 9.5.3 A Modern Perspective. 9.6 The Energy Sector and Biophysical Economic Factors. 9.6.1 Basics of Thermodynamics, Energy Flows, Work, and the Production of Wealth. 9.6.2 Energy Capture, Conversion, and Delivery to Consumers. 9.6.3 Energy Consumption: Work Processes, Efficiencies, and Waste. 9.7 Systemic Dysfunctions. 9.7.1 Values and Value Signaling. 9.7.2 Emphasis on Growth. 9.7.3 Neoliberal Capitalism. 9.8 Conclusion. 391 396 396 397 398 398 401 402 415 416 421 422 428 440 441 457 461 462 463 464 465 465 Part III Archetype Models: Complex, Adaptive, and Evolvable Systems 10 Model Archetypes for CAS, CAES. 10.1 Models of Complex Systems and Model Archetypes. 10.1.1 Representing Models. 10.1.2 Systems Dynamics Models—Simulations. 10.1.3 A General
Systems Model. 10.2 What Are Model Archetypes?. 469 469 472 472 473 473
10.2.1 The General CAS/CAES Architecture. 10.2.2 Archetype Models Overview. 10.3 Complex Adaptive and Evolvable Systems—The Archetype Model. 481 10.3.1 Complexity. 10.3.2 CAS. 10.3.3 CAES. 10.4 The CAS/CAES Framework and Prior Models. 10.4.1 Viable Systems Theory/Model. 10.4.2 Living Systems Theory—James Grier Miller. 10.4.3 Synthesis and Incorporating Other Work. 10.5 Expanding the CAS/CAES. 475 478 485 486 492 496 497 502 504 508 11 The Agent Model. 11.1 Purpose of This Chapter. 11.2 Agents. 11.2.1 The Basic Agent System. 11.2.2 Decision-Making. 11.2.3 Autonomy. 11.2.4 Ideal
Agents. 11.2.5 Agent Roles and Decision Types. 11.3 Complex Environments. 11.3.1 Uncertainty in Interactions. 11.3.2 Information Theoretical Considerations. 11.3.3 Computational Engine. 11.3.4 Decision Model. 11.4 Agency. 11.4.1 Affective and Effective Action and the Subsequent State of the Environment. 538 11.4.2 Feedback Through the Environment and the Causal Loop. 540 11.5 Complexity and Autonomy. 11.6 Conclusion. 509 509 509 510 513 519 525 526 527 527 530 531 531 538 12 The Governance Model. 12.1 Purpose of This Chapter. 12.2 The Concept of Governance. 12.2.1 The Purpose of Governance. 12.2.2 Definitions. 12.2.3
Decision Agents in Governance Systems. 12.3 Hierarchical Cybernetic Governance System (HCGS). 12.3.1 Energy Requirements Per Level. 12.3.2 Administration of Work Processes: Classical Cybernetics. 12.3.3 Operations-Level Networks: Cooperation. 12.3.4 Coordination-Level Decision Managers. 547 547 554 554 557 564 568 569 541 544 570 573 584
12.3.5 Strategie. 12.3.6 Comparing Stafford Beer’s VSM with the CAS/CAES Governance Architecture. 610 12.4 Examples of the HCGS in Nature. 12.4.1 Regulating Cellular Metabolism. 12.4.2 Regulating Multicellular Physiology. 12.4.3 The Human Brain as an HCGS. 12.5 The HCGS and Governance of the Human Social Systems. 12.5.1 Typical Government Architectures and the HCGS Model. 12.5.2 The HSS as a CAES. 12.6 Conclusion. 13 599 611 611 612 614 618 620 623 623 The Economy Model. 625 13.1 What Is an Economy?. 625 13.1.1 What Is Not in an Economy. 629 13.1.2 What Then Is an Economy?. 634 13.2 Considering a Generic Economic System. 635 13.2.1 Common Attributes of an Economy. 635 13.2.2 Economy as a Value-Adding Supply Chain. 641 13.2.3 Market Dynamics. 644 13.2.4 Governance
Processes. 649 13.2.5 Extraction of Resources. 653 13.2.6 Production of Useful Goods and Services. 657 13.2.7 Distribution—Moving Atoms, Energies,and Bits. 660 13.2.8 Consumption. 661 13.2.9 Exporting Products and Wastes. 661 13.2.10 A Note on Disturbances. 662 13.3 Nested Economies. 662 13.3.1 Metabolism. 663 13.3.2 Physiology in Multicellular Organisms. 667 13.3.3 Family Economics. 671 13.4 The Economics of a CAS/CAES. 671 13.4.1 Generic Economic Archetype. 671 13.4.2 Comparisons: Natural Versus Human Economies. 676 13.4.3 Competition and Cooperation. 681 13.5 Conclusion. 682 Part IV Designing CAES Artifactual Systems 14 Complex Artifactual Systems. 14.1 The Purpose of This Chapter. 14.1.1 What Is an
Artifact?. 14.1.2 Artifact/Cultural Evolution. 14.1.3 The Artifact Creation (or Improvement) Process. 14.1.4 The Artifact Cycle. 687 687 691 692 695 696
14.2 CAS/CAES Artifacts. 14.2.1 Design and Engineering for Increasingly Complex Artifacts. 701 14.2.2 Design Considerations. 14.2.3 Design for Emergence. 14.3 Intentional Ontogenesis and Evolution. 14.3.1 Solving Problems, Expanding Capabilities. 14.3.2 Incremental Improvement as Evolution. 14.3.3 Admitting Evolution into the Design and Engineering Process. 721 14.4 Conclusion. 700 712 714 715 716 721 722 15 Designing Complex, Adaptive, and Evolvable Systems. 725 15.1 The Purpose of This Chapter. 725 15.2 Process of System Design and Engineering. 729 15.2.1 How Do We Design Complex Systems?. 15.2.2 CAES Archetype As Template. 15.3 Designing the Food-Producing Module. 15.3.1 The Agri-Village. 15.3.2 Purposes. 15.3.3 Environment—Level-1 . 15.3.4 Input/Output—-Level
0. 15.3.5 Internal Processes—Leveli. 15.3.6 Discussion. 15.4 Conclusion. 16 729 734 743 745 746 748 752 754 757 758 759 759 16.2 Systems Design for the Human Social System. 762 16.2.1 Considering the Current Realization of CAES Subsystems. 763 16.2.2 An Architectural Design for the HSS. 773 16.3 Designing a Human Social System as a Complex Adaptive and Evolvable System. 776 16.3.1 Designing for Faulty Agents. 777 16.3.2 Designing a Sustainable Economy. 779 16.3.3 Social Organization. 790 16.3.4 Governance. 794 16.4 Conclusion. 803 Societal Systems. 16.1 Purpose of This Chapter. Bibliography. 805 |
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| id | DE-604.BV048643705 |
| illustrated | Illustrated |
| index_date | 2024-07-03T21:18:27Z |
| indexdate | 2024-07-10T09:44:54Z |
| institution | BVB |
| isbn | 9783030934811 |
| language | English |
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| physical | xxi, 814 Seiten Illustrationen, Diagramme |
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| spelling | Mobus, George E. Verfasser (DE-588)1102541958 aut Systems science theory, analysis, modeling, and design George E. Mobus Cham Springer [2022] xxi, 814 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Systemtheorie (DE-588)4058812-9 gnd rswk-swf Komplexes System (DE-588)4114261-5 gnd rswk-swf Systemforschung (DE-588)4249326-2 gnd rswk-swf Systementwicklung (DE-588)4126945-7 gnd rswk-swf Systemtheorie (DE-588)4058812-9 s Komplexes System (DE-588)4114261-5 s DE-604 Systemforschung (DE-588)4249326-2 s Systementwicklung (DE-588)4126945-7 s Erscheint auch als Online-Ausgabe 9783030934828 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=034018579&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Mobus, George E. Systems science theory, analysis, modeling, and design Systemtheorie (DE-588)4058812-9 gnd Komplexes System (DE-588)4114261-5 gnd Systemforschung (DE-588)4249326-2 gnd Systementwicklung (DE-588)4126945-7 gnd |
| subject_GND | (DE-588)4058812-9 (DE-588)4114261-5 (DE-588)4249326-2 (DE-588)4126945-7 |
| title | Systems science theory, analysis, modeling, and design |
| title_auth | Systems science theory, analysis, modeling, and design |
| title_exact_search | Systems science theory, analysis, modeling, and design |
| title_exact_search_txtP | Systems science theory, analysis, modeling, and design |
| title_full | Systems science theory, analysis, modeling, and design George E. Mobus |
| title_fullStr | Systems science theory, analysis, modeling, and design George E. Mobus |
| title_full_unstemmed | Systems science theory, analysis, modeling, and design George E. Mobus |
| title_short | Systems science |
| title_sort | systems science theory analysis modeling and design |
| title_sub | theory, analysis, modeling, and design |
| topic | Systemtheorie (DE-588)4058812-9 gnd Komplexes System (DE-588)4114261-5 gnd Systemforschung (DE-588)4249326-2 gnd Systementwicklung (DE-588)4126945-7 gnd |
| topic_facet | Systemtheorie Komplexes System Systemforschung Systementwicklung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=034018579&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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