Dynamics of Information Systems

by Hirsch, Michael J.; Pardalos, Panos M.; Murphey, Robert

• ISBN13: 9781441956880
• ISBN10: 1441956883
• Edition: 1st
• Format: Hardcover
• Copyright: 2010-04-20
• Publisher: Springer Verlag

Summary

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.This volume is intended for graduate students and researchers interested in the most recent developments in information theory and dynamical systems, as well as applied scientists interested in the application of these principles to their own area of study.

Table of Contents

Preface	p. v
The Role of Dynamics in Extracting Information Sparsely Encoded in High Dimensional Data Streams	p. 1
Introduction	p. 1
Key Subproblems Arising in the Context of Dynamic Information Extraction	p. 2
Nonlinear Embedding of Dynamic Data	p. 5
Structure Extraction from High Dimensional Data Streams	p. 7
Robust Dynamic Data Segmentation	p. 10
Example 1: Video Segmentation	p. 13
Example 2: Segmentation of Dynamic Textures	p. 15
Constrained Interpolation of High Dimensional Signals	p. 17
Hypothesis Testing and Data Sharing	p. 20
Conclusions	p. 25
References	p. 25
Information Trajectory of Optimal Learning	p. 29
Introduction	p. 29
Topology and Geometry of Learning Systems	p. 32
Problem Statement and Basic Concepts	p. 32
Asymmetric Topologies and Gauge Functions	p. 34
Trajectories Continuous in Information	p. 35
Optimal Evolution and Bounds	p. 37
Empirical Evaluation on Learning Agents	p. 40
Conclusion	p. 43
References	p. 44
Performance-Information Analysis and Distributed Feedback Stabilization in Large-Scale Interconnected Systems	p. 45
Introduction	p. 45
Problem Formulation	p. 48
Performance-Information Analysis	p. 52
Problem Statements	p. 62
Distributed Risk-Averse Feedback Stabilization	p. 74
Conclusions	p. 80
References	p. 81
A General Approach for Modules Identification in Evolving Networks	p. 83
Introduction	p. 84
Preliminaries and Problem Definition	p. 85
Preliminaries	p. 85
Problem Definition	p. 86
Compact Representation of a Network	p. 86
Structure Preservation	p. 88
Size of the Compact Representation	p. 91
Partition Based on Evolution History	p. 92
Algorithm	p. 93
Complexity	p. 95
Experimental Evaluation	p. 96
Conclusions	p. 99
References	p. 99
Topology Information Control in Feedback Based Reconfiguration Processes	p. 101
Introduction and Motivation	p. 101
Group Communication Networking	p. 103
Reconfiguration Process Optimization	p. 108
Topology Information Model	p. 108
Information Control Problem	p. 111
Topology Information Control	p. 113
Lagrangian Solution	p. 113
Distributed Implementation	p. 116
Summary of Computational Results	p. 120
Concluding Remarks	p. 122
References	p. 123
Effect of Network Geometry and Interference on Consensus in Wireless Networks	p. 125
Introduction	p. 125
Problem Formulation	p. 126
Analysis of a Ring and a 2D Torus	p. 129
The 1-D Case: Nodes on a Ring	p. 129
Nodes on a Two-Dimensional Torus	p. 132
Hierarchical Networks	p. 138
Conclusions	p. 141
References	p. 142
Analyzing the Theoretical Performance of Information Sharing	p. 145
Introduction	p. 145
Information Sharing	p. 147
Token Algorithms	p. 148
Experimental Results	p. 149
Optimality of the Lookahead Policy	p. 150
Optimality of the Random Policies	p. 151
Effects of Noisy Estimation	p. 152
Properties Affecting Optimality	p. 154
Scaling Network Size	p. 156
Related Work	p. 161
Conclusions and Future Work	p. 162
References	p. 163
Self-Organized Criticality of Belief Propagation in Large Heterogeneous Teams	p. 165
Introduction	p. 165
Self-Organized Criticality	p. 167
Belief Sharing Model	p. 168
System Operation Regimes	p. 169
Simulation Results	p. 170
Related Work	p. 181
Conclusions and Future Work	p. 182
References	p. 182
Effect of Humans on Belief Propagation in Large Heterogeneous Teams	p. 183
Introduction	p. 183
Self-Organized Critical Systems	p. 185
The Enabler-Impeder Effect	p. 185
Model of Information Dissemination in a Network	p. 186
Simulation Results	p. 187
Related Work	p. 194
Conclusion and Future Work	p. 195
References	p. 195
Integration of Signals in Complex Biophysical Systems	p. 197
Introduction	p. 198
Methods for Analysis of Phase Synchronization	p. 199
Instantaneous Phase	p. 199
Phase Synchronization	p. 201
Generalized Phase Synchronization	p. 201
Analysis of the Data Collected During Sensory-Motor Experiments	p. 203
Sensory-Motor Experiments and Neural Data Acquisition	p. 203
Computational Analysis of the LFP Data	p. 204
Conclusion	p. 209
References	p. 210
An Info-Centric Trajectory Planner for Unmanned Ground Vehicles	p. 213
Introduction	p. 213
Problem Formulation and Background	p. 215
Obstacle Motion Studies	p. 217
The Sliding Door	p. 217
The Cyclic Sliding Door	p. 219
Obstacle Crossing (No Intercept)	p. 224
Obstacle Intercept	p. 225
Obstacle Intercept Window	p. 226
Target Motion Studies	p. 228
Target Rendezvous: Vehicle Faster than Target	p. 228
Target Rendezvous: Vehicle Slower than Target	p. 229
Target Rendezvous: Variable Target Motion	p. 230
Conclusion	p. 231
References	p. 231
Orbital Evasive Target Tracking and Sensor Management	p. 233
Introduction	p. 233
Fundamentals of Space Target Orbits	p. 235
Time and Coordinate Systems	p. 235
Orbital Equation and Orbital Parameter Estimation	p. 235
Modeling Maneuvering Target Motion in Space Target Tracking	p. 237
Sensor Measurement Model	p. 237
Game Theoretic Formulation for Target Maneuvering Onset Time	p. 238
Nonlinear Filter Design for Space Target Tracking	p. 238
Posterior Cramer-Rao Lower Bound of the State Estimation Error	p. 240
Sensor Management for Situation Awareness	p. 241
Information Theoretic Measure for Sensor Assignment	p. 241
Covariance Control for Sensor Scheduling	p. 242
Game Theoretic Covariance Prediction for Sensor Management	p. 243
Simulation Study	p. 244
Scenario Description	p. 244
Performance Comparison	p. 245
Summary and Conclusions	p. 247
References	p. 254
Decentralized Cooperative Control of Autonomous Surface Vehicles	p. 257
Introduction	p. 257
Motivation	p. 258
Decentralized Hierarchical Supervisor	p. 258
Persistent ISR Task	p. 261
Transit	p. 264
Simulation Results	p. 270
Conclusion and Future Work	p. 272
References	p. 273
A Connectivity Reduction Strategy for Multi-agent Systems	p. 275
Introduction	p. 275
Background	p. 276
Model	p. 276
Edge Robustness	p. 277
A Distributed Scheme of Graph Reduction	p. 278
Redundant Edges and Triangle Closures	p. 279
Local Triangle Topologies	p. 280
Distributed Algorithm	p. 281
Discussion and Simulation	p. 284
Conclusion	p. 286
References	p. 286
The Navigation Potential of Ground Feature Tracking	p. 287
Introduction	p. 287
Modeling	p. 289
Special Cases	p. 292
Nondimensional Variables	p. 295
Observability	p. 297
Only the Elevation zp of the Tracked Ground Object is Known	p. 300
Partial Observability	p. 302
Conclusion	p. 302
References	p. 303
Minimal Switching Time of Agent Formations with Collision Avoidance	p. 305
Introduction	p. 305
Problem Definition	p. 308
Dynamic Programming Formulation	p. 310
Derivation of the Dynamic Programming Recursion	p. 310
Collision Avoidance	p. 311
Computational Implementation	p. 313
Computational Experiments	p. 317
Conclusion	p. 319
References	p. 320
A Moving Horizon Estimator Performance Bound	p. 323
Introduction	p. 323
Linear State Estimation	p. 324
Kalman Filter as an IIR Filter	p. 325
Moving Average Implementation	p. 326
MHE Performance Bound	p. 327
Situation When A - K H A ≥ 1	p. 329
Alternative Derivation	p. 329
Simulation and Analysis	p. 330
Simulation of Moving Horizon Estimator and Error Bound	p. 330
Monte Carlo Analysis of Error Bound	p. 332
Future Work	p. 334
References	p. 334
A p-norm Discrimination Model for Two Linearly Inseparable Sets	p. 335
Introduction	p. 335
The p-norm Linear Separation Model	p. 337
Implementation of p-order Conic Programming Problems via Polyhedral Approximations	p. 341
Polyhedral Approximations of p-order Cones	p. 343
"Tower-of-Variables" (Ben-Tal and Nemirovski [4])	p. 344
Polyhedral Approximations of 3-dimensional p-order Cones	p. 346
Case Study	p. 349
Conclusions	p. 351
References	p. 351
Local Neighborhoods for the Multidimensional Assignment Problem	p. 353
Introduction	p. 353
Neighborhoods	p. 355
Intrapermutation Exchanges	p. 356
Interpermutation Exchanges	p. 361
Extensions	p. 364
Variable Depth Interchange	p. 364
Path Relinking	p. 364
Variable Neighborhood	p. 368
Discussion	p. 369
References	p. 370
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