Agent-Directed Simulation and Systems Engineering (Wiley Series in Systems Engineering and Management)

Agent-Directed Simulation and Systems Engineering......Page 2
Foreword......Page 10
Contents......Page 12
Preface......Page 22
List of Contributors......Page 26
Part One Background......Page 30
1.1 Introduction......Page 32
1.2.1 Purpose of Use......Page 33
1.2.2 Problem to Be Solved......Page 37
1.2.4 M&S as a Type of Knowledge Processing......Page 38
1.3 Model-Based Activities......Page 42
1.3.3 Model Processing......Page 44
1.3.4 Behavior Generation......Page 46
1.5 Advancement of M&S......Page 49
1.6 Preeminence of M&S......Page 53
1.6.2 Knowledge-Based or Soft Tools......Page 56
1.6.3 Knowledge Generation Tools......Page 59
1.7 Summary and Conclusions......Page 61
2.1 Introduction......Page 66
2.2 Perspective and Background on Autonomic Systems......Page 68
2.3.1 Motivating Scenario: Adaptive Experience Management in Distributed Mission Training......Page 70
2.3.2 An Architectural Framework for Decentralized Autonomic Simulation Systems......Page 71
2.3.3 Challenges and Issues......Page 73
2.4 Symbiotic Adaptive Multisimulation: An Autonomic Simulation System......Page 76
2.4.1 Metamodels for Introspection Layer Design......Page 77
2.4.2 Local Adaptation: First-Order Change via Particle Swarm Optimizer......Page 79
2.4.3 The Learning Layer: Genetic Search of Potential System Configurations......Page 80
2.4.4 SAMS Component Architecture......Page 81
2.5 Case Study: UAV Search and Attack Scenario......Page 84
2.5.1 Input Factors......Page 85
2.5.2 Agent Specifications......Page 86
2.6 Validation and Preliminary Experimentation with SAMS......Page 93
2.6.1 Face Validity of the UAV Model......Page 94
2.6.2 Experiments with the Parallel SAMS Application......Page 96
2.7 Summary......Page 99
Part Two Agents and Modeling and Simulation......Page 102
3.1 Introduction......Page 104
3.2.1 Defining Agents......Page 105
3.2.2 Situated Environment and Agent Society......Page 107
3.3.1 Realizing Situatedness......Page 108
3.3.2 Realizing Autonomy......Page 110
3.3.3 Realizing Flexibility......Page 111
3.3.4 Architectures and Characteristics......Page 113
3.4 Agenthood Implications for Practical Applications......Page 115
3.4.1 Systems Engineering, Simulation, and Agents......Page 116
3.4.2 Modeling and Simulating Human Behavior for Systems Engineering......Page 117
3.4.3 Simulation-Based Testing in Systems Engineering......Page 120
3.4.4 Simulation as Support for Decision Making in Systems Engineering......Page 122
3.4.5 Implications for Modeling and Simulation Methods......Page 123
3.5.1 History and Application-Specific Taxonomies......Page 125
3.5.2 Categorizing the Agent Space......Page 128
3.6 Concluding Discussion......Page 130
4.1 Introduction......Page 140
4.2.2 Complexity......Page 142
4.2.3 Complex Systems of Systems......Page 143
4.2.4 Software Agents within the Spectrum of Computational Paradigms......Page 144
4.3.1 Agent Simulation......Page 147
4.3.3 Agent-Supported Simulation......Page 148
4.4.1 A Metamodel for Agent System Models......Page 149
4.4.2 A Taxonomy for Modeling Agent System Models......Page 151
4.4.3 Using Agents as Model Design Metaphors: Agent-Based Modeling......Page 152
4.4.4 Simulation of Agent Systems......Page 156
4.5 Agent-Based Simulation......Page 158
4.5.1 Autonomic Introspective Simulation......Page 159
4.5.2 Agent-Coordinated Simulator for Exploratory Multisimulation......Page 160
4.6 Agent-Supported Simulation......Page 163
4.6.1 Agent-Mediated Interoperation of Simulations......Page 164
4.6.2 Agent-Supported Simulation for Decision Support......Page 168
4.7 Summary......Page 170
Part Three Systems Engineering and Quality Assurance for Agent-Directed Simulation......Page 174
5.1 Introduction......Page 176
5.3 Systems Engineering Definition and Attributes......Page 177
5.3.1 Knowledge......Page 178
5.3.2 People and Information Management......Page 179
5.3.3 Processes......Page 180
5.3.4 Methods and Tools......Page 185
5.4 The System Life Cycle......Page 186
5.4.1 Conceptual Design (Requirements Analysis)......Page 189
5.4.3 Detailed Design and Development......Page 190
5.4.4 Production and Construction......Page 192
5.5.1 Integrating Perspectives into the Whole......Page 193
5.5.2 Risk Management......Page 194
5.5.3 Decisions and Trade Studies (the Strength of Alternatives)......Page 195
5.5.4 Modeling and Evaluating the System......Page 197
5.6 Summary......Page 198
6.1 Introduction......Page 202
6.2 Characteristics of Open Agent Systems......Page 203
6.3 Issues in the Quality Assurance of Agent Simulations......Page 204
6.4 Large-Scale Open Complex Systems – The Network-Centric System Metaphor......Page 206
6.5 M&S Challenges for Large-Scale Open Complex Systems......Page 208
6.6 Quality Assessment of Simulations of Large-Scale Open Systems......Page 210
6.7 Conclusions......Page 215
7.1.1 The Need for a Fresh Look......Page 218
7.1.2 Basic Terms......Page 220
7.2.2 Contributions of Simulation to Failure Avoidance......Page 221
7.2.3 Need for Failure Avoidance in Simulation Studies......Page 223
7.2.4 Some Sources of Failure in M&S......Page 225
7.3.1 Types of Assessment......Page 227
7.4 Need for Multiparadigm Approach for Successful M&S Projects......Page 229
7.4.1 V&V Paradigm for Successful M&S Projects......Page 230
7.4.2 QA Paradigm for Successful M&S Projects......Page 232
7.4.4 Lessons Learned and Best Practices for Successful M&S Projects......Page 233
7.5 Failure Avoidance for Agent-Based Modeling......Page 235
7.5.1 Failure Avoidance in Rule-Based Systems......Page 236
7.5.2 Failure Avoidance in Autonomous Systems......Page 237
7.5.3 Failure Avoidance in Agents with Personality, Emotions, and Cultural Background......Page 238
7.5.4 Failure Avoidance in Inputs......Page 239
7.6 Failure Avoidance for Systems Engineering......Page 241
7.7 Conclusion......Page 242
8.1 Introduction......Page 248
8.2.2 The Functions of Systems Engineering......Page 249
8.4.1 The Role of M&S in Systems......Page 250
8.5 Toward Systems Engineering for Agent-Directed Simulation......Page 251
8.5.1 The Essence of Complex Adaptive Open Systems (CAOS)......Page 252
8.5.2 The Merits of ADS......Page 253
8.6 Sociocognitive Framework for ADS-SE......Page 254
8.6.1 Social-Cognitive View......Page 255
8.6.2 The Dimensions of Representation......Page 256
8.7 Case Study: Human-Centered Work Systems......Page 257
8.7.1 Operational Level – Organizational Subsystem......Page 258
8.7.2 Operational Level – Organizational Subsystem......Page 259
8.7.4 The Technical Level......Page 261
8.8 Conclusions......Page 264
9.1 Introduction......Page 266
9.2 Organizational Model......Page 268
9.3.1 Organizational Structures in Organization Theory......Page 269
9.3.2 Organizational Structures in Multiagent Systems......Page 270
9.4.1 Environment Characteristics......Page 271
9.4.2 Congruence......Page 273
9.5 Organization and Autonomy......Page 274
9.6.1 Organizational Utility......Page 276
9.6.2 Organizational Change......Page 277
9.7 Organizational Design......Page 279
9.7.1 Designing Organizational Simulations......Page 281
9.7.2 Application Scenario......Page 282
9.8 Understanding Simulation of Reorganization......Page 285
9.8.2 Analyzing Simulation Case Studies......Page 286
9.9 Conclusions......Page 292
10.1 Introduction......Page 298
10.2 Architectural Style for ADS......Page 300
10.3 Agent-Directed Simulation – An Overview......Page 301
10.3.1 Language......Page 302
10.3.2 Environment......Page 304
10.3.4 Application......Page 305
10.4.1 Ascape......Page 306
10.4.2 NetLogo......Page 309
10.4.3 Repast......Page 312
10.4.4 Swarm......Page 315
10.4.5 Mason......Page 318
10.5.1 Language......Page 320
10.5.2 Environment......Page 324
10.5.3 Service......Page 327
10.5.4 Application......Page 328
10.6 CASESim – A Multiagent Simulation for Cognitive Agents for Social Environment......Page 329
10.6.2 Environment......Page 331
10.6.3 Service......Page 335
10.6.4 Application......Page 339
10.7 Conclusion......Page 341
11.2 The Systems Engineering Process......Page 346
11.3 Modeling and Simulation Support......Page 347
11.4 Facilities......Page 349
11.5 An Industrial Use Case: Space Systems......Page 350
11.5.1 Simulators for Analysis and Design......Page 352
11.6 Outlook......Page 354
11.7 Conclusions......Page 356
12.1 Introduction......Page 358
12.2 New Approaches Are Needed......Page 360
12.2.1 Employing ADS Through the Framework of Empirical Relevance......Page 361
12.2.2 Simulating Systems of Systems......Page 363
12.3 Agent-Directed Simulation for the Systems Engineering of Human Complex Systems......Page 365
12.3.1 A Call for Agents in the Study of Human Complex Systems......Page 366
12.4 A Model-Centered Science of Human Complex Systems......Page 367
12.5.1 Components of the Infrastructure for Complex Systems Engineering......Page 368
12.5.3 The Genetic Algorithm Optimization Toolkit......Page 370
12.6 Case Studies......Page 373
12.6.1 Case Study 1: Defending The Stadium......Page 374
12.6.2 Case Study 2: Secondary Effects from Pandemic Influenza......Page 379
12.7 Summary......Page 384
Part Four Agent-Directed Simulation for Systems Engineering......Page 390
13.A cAutoDEVS – A Tool for the Bifurcated Methodology......Page 392
13.2 The Need for Verification Requirements......Page 393
13.3 Experimental Frames and System Entity Structures......Page 395
13.4 Decomposition and Design of System Architecture......Page 400
13.5 Employing Agents in M&S-Based Design, Verification and Validation......Page 405
13.6 Experimental Frame Concepts for Agent Implementation......Page 407
13.7 Agent-Implemented Experimental Frames......Page 410
13.8.1 Automation of Agent Attachment to System Components......Page 411
13.8.2 DEVS-Agent Communications/Coordination......Page 413
13.8.3 DEVS-Agent Endomorphic Models......Page 415
13.9 Summary and Conclusions......Page 417
14.1.1 History......Page 428
14.1.2 Motivating Agent-Directed Decision Support Simulation Systems......Page 430
14.1.3 Working Definitions......Page 432
14.2 Cognitive Foundations for Decision Support......Page 434
14.2.1 Decision Support Systems as Social Actors......Page 435
14.2.2 How to Present the System to the User and Improve Trust......Page 436
14.2.3 Relevance for the Engineer......Page 439
14.3 Technical Foundations for Decision Support......Page 440
14.3.1 Machine-Based Understanding for Decision Support......Page 441
14.3.2 Requirements for Systems When Being Used for Decision Support......Page 442
14.3.3 Agent-Directed Multimodel and Multisimulation Support......Page 446
14.3.4 Methods Applicable to Support Agent-Directed Decision Support Simulation Systems......Page 447
14.4.1 Supporting Command and Control......Page 450
14.4.2 Supporting Inventory Control and Integrated Logistics......Page 452
14.5 Conclusion......Page 455
15.1 Introduction......Page 462
15.2.1 Organization-Theoretic Perspective for Simulation-Based Analysis of Software Processes......Page 464
15.2.2 Simulation Methods for Software Process Performance Analysis......Page 465
15.3.1 Organization Structure......Page 466
15.3.2 Team-RUP Task Model......Page 467
15.3.3 Team-RUP Team Archetypes and Cooperation Mechanisms......Page 468
15.3.4 Reward Mechanism in Team-RUP......Page 469
15.4 Design and Implementation of Team-RUP......Page 470
15.4.1 Performance Metrics......Page 472
15.4.2 Validation of the Model......Page 473
15.5 Results and Discussion......Page 474
15.6 Conclusions......Page 476
16.1 Introduction......Page 480
16.1.1 Manufacturing Systems......Page 481
16.1.2 Agent-Based Modeling......Page 482
16.2 Simulation Modeling and Analysis for Manufacturing Systems......Page 483
16.2.1 Manufacturing System Design......Page 484
16.2.2 Manufacturing Operation......Page 487
16.3.1 Emergent Approaches......Page 492
16.3.2 Agent-Based Manufacturing......Page 493
16.3.3 The Holonic Approach: Hierarchic Open Agent Systems......Page 495
16.4 Summary......Page 497
17.2 Work Systems Design......Page 504
17.2.1 Existing Work System Design Methods......Page 505
17.2.2 A Brief History of Work Systems Design......Page 506
17.3.1 Designing Work Systems: What Is the Purpose and What Can Go Wrong?......Page 507
17.3.2 The Difficulty of Convincing Management......Page 508
17.4 Work Practice Modeling and Simulation......Page 509
17.4.2 Modeling Work Practice......Page 510
17.5 The Brahms Language......Page 516
17.5.1 Simulation or Execution with Brahms......Page 517
17.5.2 Modeling People and Organizations......Page 518
17.5.3 Modeling Artifacts and Data Objects......Page 519
17.5.4 Modeling Communication......Page 521
17.5.5 Modeling Location and Movement......Page 522
17.5.6 Java Integration......Page 524
17.6 Systems Engineering: From Simulation to Implementation......Page 525
17.6.1 A Cyclic Approach......Page 527
17.6.2 Modeling Current Operations......Page 528
17.6.3 Modeling Future Operations......Page 530
17.6.4 MAS Implementation......Page 531
17.7 A Case Study: The OCA Mirroring System......Page 532
17.7.1 Mission Control as a Socio-Technical Work System......Page 533
17.7.3 Simulating the Current OCA Work System......Page 534
17.7.4 Designing the Future OCA Work System......Page 539
17.7.6 Implementing OCAMS......Page 540
17.8 Conclusion......Page 543
Index......Page 546