Intelligence-Based Systems Engineering (2011) .. A. Tolk & L.C. Jain eds
Contents
Chapter 1
Towards Intelligence-Based Systems Engineering and System of Systems Engineering . . . 1
Andreas Tolk, Kevin MacG. Adams, Charles B. Keating
1 Introduction . . . 1
2 Intelligence-Based Systems . . . 2
2.1 Characteristics of Intelligence-Based Systems . . . 2
2.2 How to Capture Intelligence . . . 4
3 Systems Engineering . . . 6
3.1 Traditional Systems Engineering . . . 7
3.2 System of Systems . . . 8
3.3 System of Systems Engineering. . . 10
3.4 System of Systems Engineering Methodology . . . 11
3.5 Intelligence-Based Systems Engineering . . . 16
4 Contributions to These Topics within This Volume . . . 18
References . . . 20
Chapter 2
Future Directions for Semantic Systems . . . 23
John F. Sowa
1 The Knowledge Acquisition Bottleneck . . . 23
2 Natural Language Processing . . . 24
3 Reasoning and Problem Solving . . . 27
4 Semantic Web . . . 30
5 Language Analysis and Reasoning . . . 35
6 Integrating Semantic Systems . . . 43
References . . . 45
Chapter 3
Defining and Validating Semantic Machine to Machine Interoperability . . . 49
Claudia Szabo, Saikou Y. Diallo
1 Introduction . . . 49
2 State of the Art in Interoperability . . . 50
2.1 Semantics of Data for a Machine . . . 53
2.2 Formal Representation of Data for a Machine . . . 55
2.3 Semantic Machine to Machine Interoperability . . . 58
3 Formal Validation of Interoperable Federations . . . 63
3.1 Knowledge Representation. . . 66
3.2 Formal Validation of Model Execution . . . 68
3.3 Reference Model . . . 68
3.4 Formal Validation Process . . . 69
4 Summary and Recommendations . . . 72
References . . . 72
Chapter 4
An Approach to Knowledge Integration Applied to a Configuration Problem . . . 75
Maria Vargas-Vera, Miklos Nagy, Dietmar Jannach
1 Introduction . . . 75
2 Related Work . . . 77
2.1 Expert Systems – Knowledge Bases . . . 77
2.2 Ontologies View. . . 78
2.3 Databases . . . 80
2.4 Knowledge Management. . . 80
3 Scenario . . . 81
3.1 Constraint Satisfaction Problem (CSP) . . . 82
3.2 Case Study: Computer Configuration Problem . . . 83
3.3 Constraint Graph . . . 84
4 Mapping Process . . . 84
5 Knowledge Integration Framework . . . 92
5.1 Algorithms for Detecting and Correcting Overlappings . . . 94
6 Evaluation. . . 97
6.1 Mapping Quality . . . 99
6.2 Configuration Quality . . . 100
7 Conclusions . . . 102
References . . . 103
Chapter 5
Simulation-Based Systems Design in Multi-actor Environments . . . 107
Michele Fumarola, Mamadou D. Seck, Alexander Verbraeck
1 Introduction . . . 107
1.1 Outline of the Chapter . . . 108
2 Designing Systems . . . 108
3 Systems Approaches . . . 111
3.1 Systems Simulation in Design . . . 112
3.2 Soft Systems Methodology. . . 113
4 Designing a Multimethodological Approach . . . 118
4.1 Component Based Modeling . . . 118
4.2 Different Levels of Abstraction . . . 119
4.3 Structing Alternatives . . . 121
4.4 Participatory Design . . . 123
5 Conclusion . . . 123
References . . . 124
Chapter 6
Distributed Simulation Using RESTful Interoperability Simulation Environment (RISE) Middleware . . . 129
Khaldoon Al-Zoubi, Gabriel Wainer
1 Introduction . . . 129
2 Background on Distributed Simulation . . . 132
3 RISE Middleware API . . . 136
4 RISE-based Distributed CD++ Simulation Algorithms . . . 137
4.1 Distributed CD++ (DCD++) Architecture . . . 139
4.2 DCD++ Simulation Synchronization Algorithms . . . 143
5 Distributed Simulation Interoperability Standards . . . 148
References . . . 155
Chapter 7
Agile Net-Centric Systems Using DEVS Unified Process . . . 159
Saurabh Mittal
1 Introduction . . . 160
2 Related Technologies . . . 162
3 DEVS Unified Process with DEVS/SOA . . . 163
3.1 Discrete Event Systems Specification. . . 163
3.2 Web Services and Interoperability Using XML . . . 165
3.3 An Abstract DEVS Service Agent . . . 166
3.4 DEVS/SOA Framework for Net-Centric Modeling and Simulation. . . 166
3.5 DEVS Unified Process a.k.a DUNIP . . . 169
4 Multi-layered Agent-Based Test Instrumentation System Using GIG/SOA . . . 171
4.1 Deploying Test Agents over the GIG/SOA. . . 172
4.2 Implementation of Test Federations . . . 173
5 Abstract DEVS Service Wrapper . . . 174
6 Workflow Composition and DoDAF-Based Mission Threads . . . 175
6.1 Web Service Work Flow Formalism . . . 177
6.2 Mapping of DEVS, BPEL and DoDAF Artifacts with WSWF Formalism . . . 180
7 Case Study . . . 182
7.1 DEVS Wrapper Agent . . . 182
7.2 Workflow Design, Analysis and Execution . . . 185
8 Agility in DEVS Unified Process . . . 191
9 Conclusions and Future Work . . . 193
10 Acronyms . . . 196
References . . . 197
Chapter 8
Systems Engineering and Conversational Agents . . . 201
James O’Shea, Zuhair Bandar, Keeley Crockett
1 Introduction . . . 201
2 The Scope of CAs . . . 202
2.1 Spoken Dialogue Systems. . . 202
2.2 Chatterbots . . . 203
2.3 Natural Language Processing Based Dialogue Management Systems . . . 203
2.4 Goal-Oriented CAs . . . 204
2.5 Embodied CAs . . . 206
3 Practical Applications of CAs . . . 207
3.1 CAs for Selling . . . 207
3.2 A GO-CA Student Debt Advisor . . . 210
4 Design Methodology for GO-CAs . . . 212
4.1 Knowledge Engineering . . . 212
4.2 Implementation . . . 213
4.3 Scripting Language . . . 214
4.4 Evaluation . . . 217
4.5 Maintenance . . . 219
5 Novel Algorithms – Short Text Semantic Similarity . . . 221
5.1 The STASIS Algorithm . . . 222
5.2 Latent Semantic Analysis. . . 224
6 Research Opportunities . . . 225
7 Conclusions . . . 226
References . . . 227
Chapter 9
Advanced Concepts and Generative Simulation Formalisms for Creative Discovery Systems Engineering . . . 233
Levent Yilmaz, C. Anthony Hunt
1 Introduction . . . 233
1.1 Motivation . . . 236
1.2 Scientific Problem Solving with Computational Models . . . 236
2 Models and Principles of Creative Problem Solving . . . 239
2.1 Background . . . 239
2.2 Models of Creative Cognition . . . 240
3 Generative Parallax Simulation: Basic Concepts . . . 242
3.1 An Abstract Model of Creative Cognition . . . 242
3.2 Abstract Specification of the Structure and Dynamics of GPS . . . 243
3.3 Implications of the Ecological Perspective . . . 246
4 Meta-simulation of GPS . . . 246
4.1 Conceptual Model for GPS Simulator . . . 246
4.2 Meta-simulation Parameters . . . 249
4.3 Qualitative Analysis of Results and Discussion . . . 249
5 Discussion and Future Work . . . 255
5.1 Improving Autonomy in Schema Evolution and Diffusion . . . 255
5.2 Toward Adaptive Growth of Analogue Ensembles for Creative Discovery Systems . . . 256
5.3 Strategic and Context Sensitive Exploration . . . 256
6 Conclusions . . . 257
References . . . 257
Chapter 10
Establishing a Theoretical Baseline: Using Agent-Based Modeling to Create Knowledge . . . 259
Jose J. Padilla, Saikou Y. Diallo, Andres A. Sousa-Poza
1 Introduction . . . 259
2 Systems Engineering and Its Challenges . . . 260
3 Theory and Theory Creation. . . 263
4 Building Theory through M&S . . . 266
4.1 Existing M&S Methodologies/Methods for Theory Building . . . 270
4.2 A Methodology for Theory Building Using M&S . . . 274
4.3 Selecting the Modeling Paradigm. . . 275
5 Test Case: Building a Theory of Understanding Using Agents . . . 276
5.1 Brief on ABM and Its Relevance on Theory Building . . . 276
5.2 Importance of Understanding to Problem Situations . . . 277
5.3 Implementing the Methodology for Theory Building Using M&S . . . 277
6 Final Remarks and Conclusion . . . 281
7 List of Acronyms . . . 282
References . . . 282
Chapter 11
“The User Around the Marketplace”: Automatic Engineering of Interactive E-commerce Applications . . . 285
Mart´in L´opez-Nores, Yolanda Blanco-Fern´andez, Jos´e J. Pazos-Arias
1 Introduction . . . 285
2 Background. . . 287
3 Elements to Engineer Personalized Interactive Applications . . . 290
4 The Personalization Procedures . . . 293
4.1 Reasoning-Driven Recommendation of Items . . . 293
4.2 Composition of Interactive Commercial Applications . . . 295
4.3 Feedback . . . 296
5 Our Proposal in DTV Advertising . . . 297
5.1 A Simple Example. . . 298
5.2 Experimental Evaluation . . . 300
6 Conclusion . . . 303
References . . . 303
Chapter 12
Wireless Sensor Network Anomalies: Diagnosis and Detection Strategies . . . 309
Raja Jurdak, X. Rosalind Wang, Oliver Obst, and Philip Valencia
1 Introduction . . . 309
2 Types of WSN Anomalies . . . 310
2.1 Network Anomalies . . . 313
2.2 Node Anomalies . . . 315
2.3 Data Anomalies . . . 316
2.4 Other Anomalies . . . 318
3 Anomaly Detection Strategies . . . 318
3.1 Architecture . . . 320
3.2 Usability . . . 321
4 Design Guidelines and Conclusions . . . 323
References . . . 324
Chapter 13
Enterprise Ontologies – Better Models of Business . . . 327
Ian Bailey
1 Introduction – Intelligence-Led Systems Engineering . . . 327
1.1 Introduction – Business Ontologies . . . 329
1.2 Information System Requirements Gathering . . . 329
1.3 Driving-Out Complexity . . . 331
1.4 Stovepipes . . . 331
2 What Is Needed for Better Information Systems? . . . 332
2.1 Better Analysis – Getting Your Hands Dirty . . . 333
2.2 Flexibility – Using the Full Range of Logic . . . 334
2.3 Consistency – Sophisticated, Repeatable Analysis . . . 335
2.4 Implementation – New Ways of Storing . . . 335
3 A New Approach to Information Systems Development . . . 336
3.1 Introducing the BORO Method . . . 336
3.2 Managing Time . . . 337
4 Addressing Arguments against Ontology . . . 340
5 Conclusions . . . 341
5.1 Literature Search . . . 341
References . . . 341
Author Index . . . 343