Dynamics of Information Systems: Theory and Applications / Edition 1

by Michael Hirsch, Panos M. Pardalos, Robert Murphey

Overview

Our understanding of information and information dynamics has outgrown classical information theory. The theory does not account for the value or influence of information within the context of a system or network and does not explain how these properties might influence how information flows though and interacts with a system. The invited chapters in this collection present new theories, methods, and applications that address some of these limitations.

Dynamics of Information Systems presents state-of-the-art research explaining the importance of information in the evolution of a distributed or networked system. This book presents techniques for measuring the value or significance of information within the context of a system. Each chapter reveals a unique topic or perspective from experts in this exciting area of research.

These newly developed techniques have numerous applications including: the detection of terrorist networks, the design of highly functioning businesses and computer systems, modeling the distributed sensory and control physiology of animals, quantum entanglement and genome modeling, multi-robotic systems design, as well as industrial and manufacturing safety.

Product Details

ISBN-13:	9781441956880
Publisher:	Springer New York
Publication date:	04/09/2010
Series:	Springer Optimization and Its Applications , #40
Edition description:	2010
Pages:	372
Product dimensions:	6.30(w) x 9.20(h) x 1.00(d)

Table of Contents

Preface v

1 The Role of Dynamics in Extracting Information Sparsely Encoded in High Dimensional Data Streams Mario Sznaier Octavia Camps Necmiye Ozay Tao Ding Gilead Tadmor Dana Brooks 1

1.1 Introduction 1

1.2 Key Subproblems Arising in the Context of Dynamic Information Extraction 2

1.3 Nonlinear Embedding of Dynamic Data 5

1.4 Structure Extraction from High Dimensional Data Streams 7

1.5 Robust Dynamic Data Segmentation 10

1.5.1 Example 1: Video Segmentation 13

1.5.2 Example 2: Segmentation of Dynamic Textures 15

1.6 Constrained Interpolation of High Dimensional Signals 17

1.7 Hypothesis Testing and Data Sharing 20

1.8 Conclusions 25

References 25

2 Information Trajectory of Optimal Learning Roman V. Belavkin 29

2.1 Introduction 29

2.2 Topology and Geometry of Learning Systems 32

2.2.1 Problem Statement and Basic Concepts 32

2.2.2 Asymmetric Topologies and Gauge Functions 34

2.2.3 Trajectories Continuous in Information 35

2.3 Optimal Evolution and Bounds 37

2.4 Empirical Evaluation on Learning Agents 40

2.5 Conclusion 43

References 44

3 Performance-Information Analysis and Distributed Feedback Stabilization in Large-Scale Interconnected Systems Khanh D. Pham 45

3.1 Introduction 45

3.2 Problem Formulation 48

3.3 Performance-Information Analysis 52

3.4 Problem Statements 62

3.5 Distributed Risk-Averse Feedback Stabilization 74

3.6 Conclusions 80

References 81

4 A General Approach for Modules Identification in Evolving Networks Thang N. Dinh Incheol Shin Nhi K. Thai My T. Thai Taieb Znati 83

4.1 Introduction 84

4.2 Preliminaries and Problem Definition 85

4.2.1 Preliminaries 85

4.2.2 Problem Definition 86

4.3 Compact Representation of a Network 86

4.3.1 Structure Preservation 88

4.3.2 Size of the Compact Representation 91

4.4 Partition Based on Evolution History 92

4.4.1 Algorithm 93

4.4.2 Complexity 95

4.5 Experimental Evaluation 96

4.6 Conclusions 99

References 99

5 Topology Information Control in Feedback Based Reconfiguration Processes Alexandru Murgu Ian Postlethwaite Dawei Gu Chris Edwards 101

5.1 Introduction and Motivation 101

5.2 Group Communication Networking 103

5.3 Reconfiguration Process Optimization 108

5.3.1 Topology Information Model 108

5.3.2 Information Control Problem 111

5.4 Topology Information Control 113

5.4.1 Lagrangian Solution 113

5.4.2 Distributed Implementation 116

5.4.3 Summary of Computational Results 120

5.5 Concluding Remarks 122

References 123

6 Effect of Network Geometry and Interference on Consensus in Wireless Networks Sundaram Vanka Vijay Gupta Martin Haenggi 125

6.1 Introduction 125

6.2 Problem Formulation 126

6.3 Analysis of a Ring and a 2D Torus 129

6.3.1 The 1-D Case: Nodes on a Ring 129

6.3.2 Nodes on a Two-Dimensional Torus 132

6.4 Hierarchical Networks 138

6.5 Conclusions 141

References 142

7 Analyzing the Theoretical Performance of Information Sharing Paul Scerri Prasanna Velagapudi Katia Sycara 145

7.1 Introduction 145

7.2 Information Sharing 147

7.2.1 Token Algorithms 148

7.3 Experimental Results 149

7.3.1 Optimality of the Lookahead Policy 150

7.3.2 Optimality of the Random Policies 151

7.3.3 Effects of Noisy Estimation 152

7.3.4 Properties Affecting Optimality 154

7.3.5 Scaling Network Size 156

7.4 Related Work 161

7.5 Conclusions and Future Work 162

References 163

8 Self-Organized Criticality of Belief Propagation in Large Heterogeneous Teams Robin Glinton Praveen Paruchuri Paul Scerri Katia Sycara 165

8.1 Introduction 165

8.2 Self-Organized Criticality 167

8.3 Belief Sharing Model 168

8.4 System Operation Regimes 169

8.5 Simulation Results 170

8.6 Related Work 181

8.7 Conclusions and Future Work 182

References 182

9 Effect of Humans on Belief Propagation in Large Heterogeneous Teams Praveen Paruchuri Robin Glinton Katia Sycara Paul Scerri 183

9.1 Introduction 183

9.2 Self-Organized Critical Systems 185

9.3 The Enabler-Impeder Effect 185

9.4 Model of Information Dissemination in a Network 186

9.5 Simulation Results 187

9.6 Related Work 194

9.7 Conclusion and Future Work 195

References 195

10 Integration of Signals in Complex Biophysical Systems Alla Kammerdiner Nikita Boyko Nong Ye Jiping He Panos Pardalos 197

10.1 Introduction 198

10.2 Methods for Analysis of Phase Synchronization 199

10.2.1 Instantaneous Phase 199

10.2.2 Phase Synchronization 201

10.2.3 Generalized Phase Synchronization 201

10.3 Analysis of the Data Collected During Sensory-Motor Experiments 203

10.3.1 Sensory-Motor Experiments and Neural Data Acquisition 203

10.3.2 Computational Analysis of the LFP Data 204

10.4 Conclusion 209

References 210

11 An Info-Centric Trajectory Planner for Unmanned Ground Vehicles Michael A. Hurni Pooya Sekhavat I. Michael Ross 213

11.1 Introduction 213

11.2 Problem Formulation and Background 215

11.3 Obstacle Motion Studies 217

11.3.1 The Sliding Door 217

11.3.2 The Cyclic Sliding Door 219

11.3.3 Obstacle Crossing (No Intercept) 224

11.3.4 Obstacle Intercept 225

11.3.5 Obstacle Intercept Window 226

11.4 Target Motion Studies 228

11.4.1 Target Rendezvous: Vehicle Faster than Target 228

11.4.2 Target Rendezvous: Vehicle Slower than Target 229

11.4.3 Target Rendezvous: Variable Target Motion 230

11.5 Conclusion 231

References 231

12 Orbital Evasive Target Tracking and Sensor Management Huimin Chen Genshe Chen Dan Shen Erik P. Blasch Khanh Pham 233

12.1 Introduction 233

12.2 Fundamentals of Space Target Orbits 235

12.2.1 Time and Coordinate Systems 235

12.2.2 Orbital Equation and Orbital Parameter Estimation 235

12.3 Modeling Maneuvering Target Motion in Space Target Tracking 237

12.3.1 Sensor Measurement Model 237

12.3.2 Game Theoretic Formulation for Target Maneuvering Onset Time 238

12.3.3 Nonlinear Filter Design for Space Target Tracking 238

12.3.4 Posterior Cramer-Rao Lower Bound of the State Estimation Error 240

12.4 Sensor Management for Situation Awareness 241

12.4.1 Information Theoretic Measure for Sensor Assignment 241

12.4.2 Covariance Control for Sensor Scheduling 242

12.4.3 Game Theoretic Covariance Prediction for Sensor Management 243

12.5 Simulation Study 244

12.5.1 Scenario Description 244

12.5.2 Performance Comparison 245

12.6 Summary and Conclusions 247

References 254

13 Decentralized Cooperative Control of Autonomous Surface Vehicles Pedro DeLima Dimitri Zarzhitsky Daniel Pack 257

13.1 Introduction 257

13.2 Motivation 258

13.3 Decentralized Hierarchical Supervisor 258

13.3.1 Persistent ISR Task 261

13.3.2 Transit 264

13.4 Simulation Results 270

13.5 Conclusion and Future Work 272

References 273

14 A Connectivity Reduction Strategy for Multi-agent Systems Xiaojun Geng David Jeffcoat 275

14.1 Introduction 275

14.2 Background 276

14.2.1 Model 276

14.2.2 Edge Robustness 277

14.3 A Distributed Scheme of Graph Reduction 278

14.3.1 Redundant Edges and Triangle Closures 279

14.3.2 Local Triangle Topologies 280

14.3.3 Distributed Algorithm 281

14.4 Discussion and Simulation 284

14.5 Conclusion 286

References 286

15 The Navigation Potential of Ground Feature Tracking Meir Pachter Güner Mutlu 287

15.1 Introduction 287

15.2 Modeling 289

15.3 Special Cases 292

15.4 Nondimensional Variables 295

15.5 Observability 297

15.6 Only the Elevation z_p of the Tracked Ground Object is Known 300

15.7 Partial Observability 302

15.8 Conclusion 302

References 303

16 Minimal Switching Time of Agent Formations with Collision Avoidance Dalila B.M.M. Fontes Fernando A.C.C. Fontes 305

16.1 Introduction 305

16.2 Problem Definition 308

16.3 Dynamic Programming Formulation 310

16.3.1 Derivation of the Dynamic Programming Recursion 310

16.3.2 Collision Avoidance 311

16.4 Computational Implementation 313

16.5 Computational Experiments 317

16.6 Conclusion 319

References 320

17 A Moving Horizon Estimator Performance Bound Nicholas R. Gans Jess W. Curtis 323

17.1 Introduction 323

17.2 Linear State Estimation 324

17.2.1 Kalman Filter as an IIR Filter 325

17.2.2 Moving Average Implementation 326

17.3 MHE Performance Bound 327

17.3.1 Situation When A - K H A ≥ 1 329

17.3.2 Alternative Derivation 329

17.4 Simulation and Analysis 330

17.4.1 Simulation of Moving Horizon Estimator and Error Bound 330

17.4.2 Monte Carlo Analysis of Error Bound 332

17.5 Future Work 334

References 334

18 A p-norm Discrimination Model for Two Linearly Inseparable Sets Pavlo Krokhmal Robert Murphey Panos M. Pardalos Zhaohan Yu 335

18.1 Introduction 335

18.2 The p-norm Linear Separation Model 337

18.3 Implementation of p-order Conic Programming Problems via Polyhedral Approximations 341

18.3.1 Polyhedral Approximations of p-order Cones 343

18.3.2 "Tower-of-Variables" (Ben-Tal and Nemirovski [4]) 344

18.3.3 Polyhedral Approximations of 3-dimensional p-order Cones 346

18.4 Case Study 349

18.5 Conclusions 351

References 351

19 Local Neighborhoods for the Multidimensional Assignment Problem Eduardo L. Pasiliao Jr. 353

19.1 Introduction 353

19.2 Neighborhoods 355

19.2.1 Intrapermutation Exchanges 356

19.2.2 Interpermutation Exchanges 361

19.3 Extensions 364

19.3.1 Variable Depth Interchange 364

19.3.2 Path Relinking 364

19.3.3 Variable Neighborhood 368

19.4 Discussion 369

References 370