The complex behavior of systems in nature is rooted in intricate mechanisms of interaction that often supersede human-made systems in terms of reliability, power efficiency, and computational capacity. Researchers have begun to realize that natural systems are a great source of inspiration for novel algorithms in computation and communication systems. The International Workshop on Natural Computing (IWNC) is a platform that brings together computer scientists, biologists, mathematicians, electronic engineers, physicists, and social scientists to critically assess present findings in the field and to outline future developments in novel and emerging paradigms of computation and computing architectures. This compilation contains the papers from the most recent workshop, held in Himeji, Japan. Presented by scientists of worldwide reputation, the topics include DNA computation, cellular automata, physics and computation, evolutionary computing, neural networks, amoeba-based computing, artificial chemistry, noise-driven computing, chaotic systems, and unconventional models of communication.
Author(s): Ferdinand Peper, Hiroshi Umeo, Nobuyuki Matsui, Teijiro Isokawa
Series: Proceedings in Information and Communications Technology
Edition: 1st Edition.
Publisher: Springer
Year: 2010
Language: English
Pages: 401
Springer - Natural Computing IV (2010) (ATTiCA)......Page 3
Preface......Page 5
Table of Contents......Page 9
Introduction......Page 13
Universality and Computability......Page 14
Molecular Cellular Automaton Rules......Page 15
Dirichlet Tessellation (DT) or Voronoi Decomposition......Page 16
Information Writing, Storage and Retrieval......Page 17
Coalescence and Giant Explosion......Page 19
Density Classification Task (DCT)......Page 20
Multi-agent Robotics......Page 21
Ant Colony......Page 22
Chemotaxis......Page 23
Noise-Based Logic and Computing: From Boolean Logic Gates to Brain Circuitry and Its Possible Hardware Realization......Page 25
Embodied Computation......Page 35
Artificial Morphogenesis......Page 37
Requirements for a Formalism......Page 38
Approach......Page 39
Example......Page 43
Introduction......Page 46
Why Bio-inspired Approaches?......Page 47
Attractor Selection Principle and Its Application to Networking Problems......Page 50
Concluding Remarks......Page 52
Introduction......Page 54
Time Course of Two Connections between Two FSs in Relation to Food Amount at FS......Page 56
Maze-Solving......Page 57
Not Only the Final Answer But Also Transient......Page 59
Mathematical Formulation of Network Dynamics Adaptable to Streaming......Page 60
Risk-Minimum Path in an Inhomogeneous Field......Page 62
Effect of Food Amount on Tube Selection between Two FSs......Page 63
Concluding Remarks: Possibility of Physarum Computing......Page 64
Systems Based on Deoxyribozyme-Based Logic Gates......Page 67
Spider-Based System......Page 72
Conclusions......Page 74
Introduction......Page 76
Distributed Service Composition......Page 77
Community......Page 78
Community Structure and Formation......Page 79
Simulation and Results......Page 80
Conclusion......Page 82
Introduction......Page 84
A Brownian Cellular Automaton Model......Page 85
Embedding Delay-Insensitive Circuits into Brownian Cellular Automaton......Page 89
Implementing Ratchets with Various Configurations......Page 91
Conclusions......Page 92
Overview of a Molecular Communication System......Page 94
Molecular Communication Interface......Page 96
Molecular Propagation System......Page 97
Sender and Receiver......Page 99
Conclusions......Page 100
Introduction......Page 102
The Model System: Neuronal Maps......Page 103
Relaxation Time......Page 104
Nonlocal Coupling......Page 105
Asynchronous Updating......Page 106
Dynamic Logic Cell......Page 107
Conclusion......Page 108
Introduction......Page 111
Rotary Element......Page 112
Implementation of Rotary Element......Page 113
Delay Element and C-JOIN......Page 116
Concluding Remarks......Page 117
Introduction......Page 119
On Delay Insensitive Circuits......Page 120
Implementing DI-Circuits on Asynchronous CA......Page 121
Conclusions and Discussion......Page 126
Introduction......Page 129
Parameter-Free Genetic Algorithm......Page 130
Mutation Rate Coding......Page 131
Extended Selection Rule......Page 132
Experiments......Page 133
Conclusion and Discussion......Page 134
Introduction......Page 137
Description of the Model......Page 138
Temperature......Page 139
Growth and Death Rate of Olive Fruit Flies......Page 140
Results......Page 141
Conclusions......Page 143
Computing by Observing......Page 145
Preliminaries......Page 147
Computing by Observing Changes......Page 148
The Power of Change-Observing Acceptors......Page 150
Conclusion......Page 151
Introduction......Page 153
The Model......Page 154
Effect of Noise......Page 155
Holes and Missing Links......Page 156
Changing the Topology......Page 157
The Inverse Proportionality Law......Page 158
Conclusion......Page 160
Introduction......Page 161
The Permutation Problem......Page 162
Calculating the Probability of Genotypic Permutations......Page 163
Calculating the Probability of Phenotypic Permutations......Page 165
Discussion......Page 166
Conclusions and Future Work......Page 167
Introduction......Page 169
Structural Description......Page 170
Designing Shapes and Patterns......Page 171
Conclusion......Page 175
Introduction......Page 177
The Device......Page 178
The Modified Device......Page 179
Finding the Solution Subset......Page 183
Conclusion and Future Work......Page 184
Introduction......Page 186
DNA XOR One-Time-Pad Cryptosystem with Random Hybridization......Page 187
Message Encryption......Page 188
Random Tiling Operation......Page 189
Extraction of Cipher Strings and Key Strings......Page 190
Analysis on Error Tolerance......Page 193
Conclusion......Page 194
Introduction......Page 196
Period 1 Bugs......Page 197
Bugs with Longer Period......Page 199
Experimental Results of Collisions of Bugs......Page 200
Conclusion......Page 201
Two-Dimensional OV Model......Page 203
Linear Analysis......Page 204
Transverse Mode along the x-Axis......Page 206
Longitudinal Mode along the y-Axis......Page 207
Elliptically Polarized Mode......Page 208
Phase Diagrams......Page 209
Square......Page 210
Introduction......Page 211
Minimum Reduce Hypervolume......Page 213
Differential Evolution for MOPs by Uniform Design and Minimum Reduce Hypervolume......Page 214
Experiment Results......Page 215
Conclusion and Further Research......Page 219
Introduction......Page 221
Chaotic Neuron Model......Page 222
Noise-Induced Order in Chaotic Neuron Model......Page 223
Summary......Page 227
Introduction......Page 230
Problem Settings......Page 231
Result......Page 232
Difficulties of Original GE......Page 233
Problem Setting......Page 234
Syntax and Parameters......Page 235
Conclusion......Page 236
Introduction......Page 238
Time-Dependent QW......Page 239
Two-Period QW......Page 241
Case 1......Page 243
Case 2......Page 245
Conclusion and Discussion......Page 246
Introduction......Page 248
Model......Page 249
Mean-Field Theory......Page 250
Steady-State Density......Page 251
Results of Simulation Experiment......Page 252
Discussions and Conclusion......Page 253
Introduction......Page 256
Modeling......Page 257
Simulations and Theoretical Calculation......Page 258
Conclusive Discussion......Page 263
Introduction......Page 264
Preliminaries......Page 265
Direct Simulation of an RE by 3-Symbol RLEMs......Page 267
Concluding Remarks......Page 271
Introduction: Pump Current......Page 272
Simple Model for the Pumping Phenomenon......Page 274
Counting Statistics......Page 275
Interpretation as a Shrödinger-Like Equation......Page 276
Geometrical Phase Interpretation......Page 277
Discussion: Pump Current as a Signal Transformation......Page 278
Concluding Remarks......Page 279
Introduction......Page 280
Steady-State (SS)SS.......Page 281
Grid-Oriented-Deletion (GOD).......Page 282
Experimental Settings......Page 283
Experimental Results......Page 284
Discussion......Page 285
Conclusions......Page 287
Introduction......Page 288
Photonic DNA Automaton......Page 290
A Method for Controlling Position of DNA......Page 292
Experiments......Page 295
Conclusions......Page 299
Fluctuation Induced Structure in Chemical Reaction with Small Number of Molecules......Page 302
Introduction......Page 310
Nanophotonic Matching Utilizing Macro-scale Observation of Optical Near-Field Interactions......Page 312
Transcription Based on Photoinduced Phase Transition......Page 316
Conclusions......Page 318
Introduction......Page 320
New Compressible Fluid Model Based on Experimental Data......Page 322
Reductive Perturbation Analysis......Page 324
Conclusion......Page 327
Introduction......Page 328
Functional Sized Population MOA (FSMOA)......Page 329
Finding the Best Parameters......Page 333
Experimental Results......Page 334
Conclusion......Page 335
Ad Hoc Cellular Automata with Intra-agent Dynamics......Page 337
Emergence and Collapse of Complex/Periodic Patterns......Page 339
Emergence and Collapse of Clusters in Rule-Entry Space......Page 341
Classifying ACA......Page 342
Discussion and Conclusion......Page 343
Introduction......Page 345
Overview of Shinahr's Time-Optimum Algorithm......Page 346
Construction of Real-Coded Transition Rule Set for ABS......Page 348
Discussions......Page 352
Firing Squad Synchronization Problem on Two-Dimensional Arrays......Page 354
Delayed Synchronization Scheme for One-Dimensional Arrays......Page 355
Starting Synchronization Process......Page 357
Synchronization of Li......Page 359
Synchronization of Rectangle Longer Than Wide......Page 360
Conclusions......Page 362
Introduction......Page 364
Machine Condition Monitoring System Model......Page 365
Quaternion Based Thermal Image Correlator......Page 366
Max-Product Fuzzy Neural Network Classifier......Page 368
Experimental Results......Page 370
Conclusion......Page 373
Introduction......Page 375
Network Structure and Neuron Ensembles......Page 376
Simulation Experiment with a WS Network Structure......Page 379
Summary......Page 381
Introduction......Page 384
Distance Introduced Fork-Type Queueing System: D-Fork......Page 385
Update Rules......Page 386
Stationary Equations......Page 387
Keep One Person Waiting at the Window: D-Fork-Wait......Page 388
Theoretical Analysis and Simulation......Page 389
Experiments......Page 390
Conclusion......Page 391
Introduction......Page 392
Linkage Equilibrium......Page 393
With Mutation......Page 394
Calculation of Success Probability......Page 395
Results......Page 396
Summary and Discussion......Page 398
Author Index......Page 400
