Adaptive networks: theory, models and applications
Gespeichert in:
| Weitere Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Dordrecht [u.a.]
Springer
2009
|
| Schriftenreihe: | Understanding complex systems
Springer complexity New England Complex Systems Institute book series |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XIX, 332 S. graph. Darst. |
| ISBN: | 9783642012839 9783642012846 |
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Datensatz im Suchindex
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|---|---|
| adam_text | Titel: Adaptive networks
Autor: Groß, Thilo
Jahr: 2009
Contents
1 Adaptive Networks............................................. 1
Thilo Gross and Hiroki Sayama
1.1 Introduction............................................... 1
1.2 The Interplay Between State and Topology..................... 2
1.3 Timescale Separation and Critical Phenomena.................. 3
1.4 Self-Organization of Non-trivial Network Topologies............ 4
1.5 Adaptive Networks with Inseparable Timescales................ 5
1.6 In this Book............................................... 6
References..................................................... 8
Part I Real-World Examples of Adaptive Networks
2 Social Group Dynamics in Networks ............................. 11
Gergely Palla, Peter Pollner, Albert-Laszlo Barabasi, and Tamas Vicsek
2.1 Introduction............................................... 11
2.2 Construction of the Networks................................ 13
2.3 Finding Communities....................................... 15
2.3.1 The Clique Percolation Method....................... 15
2.3.2 Preferential Attachment at the Level of Communities..... 16
2.3.3 The Static Communities ............................. 20
2.3.4 Validating the Communities .......................... 22
2.4 Evolving Communities...................................... 24
2.5 Statistical Properties of the Community Dynamics............... 27
2.5.1 Basic Statistics..................................... 27
2.5.2 Stationarity and Lifetime............................. 29
2.5.3 Predicting Community Break Up...................... 30
2.5.4 Merging of Communities............................. 32
2.6 Conclusion................................................ 34
References..................................................... 35
* Contents
3 Time-Dependent Complex Networks: Dynamic Centrality, Dynamic
Motifs, and Cycles of Social Interactions.......................... 39
Dan Braha and Yaneer Bar-Yam
3.1 Dynamic Centrality in Large-Scale Communication Networks..... 39
3.2 Dynamic Centrality in Spatial Proximity Social Networks........ 44
3.3 Dynamic Network Motifs and Cycles of Social Interaction........ 46
3.4 Summary................................................. 48
References..................................................... 49
4 Adaptive Biological Networks ................................... 51
Mark D. Fricker, Lynne Boddy, Toshiyuki Nakagaki, and Daniel P.
Bebber
4.1 Introduction............................................... 51
4.2 Network Development in Mycelial Fungi...................... 52
4.3 Predicted Transport Characteristics of the Mycelial Network...... 54
4.4 Comparison Between Predicted Transport
and Experimental Transport................................. 58
4.5 Oscillations and Pulsatile Transport........................... 58
4.6 Network Robustness........................................ 61
4.7 Simple Networks in the Plasmodial Slime Mould Physarum
Polycephalum ............................................ 61
4.8 Universal Features of Biological Networks?.................... 65
References..................................................... 67
Part II Self-Organization of Adaptive Networks
5 Self-Organized Criticality and Adaptation in Discrete Dynamical
Networks ..................................................... 73
Thimo Rohlf and Stefan Bornholdt
5.1 Introduction............................................... 73
5.2 Dynamics of Random Boolean Networks and Random Threshold
Networks................................................ 77
5.2.1 Underlying Graph Structure .......................... 77
5.2.2 Random Boolean Networks........................... 79
5.2.3 Random Threshold Networks......................... 79
5.2.4 Basic Dynamical Properties of RBNs and RTNs ......... 80
5.3 Network Self-Organization from Co-evolution of Dynamics and
Topology................................................ 83
5.3.1 Activity-Dependent Rewiring......................... 83
5.3.2 Adaptive Thresholds - Time Scale Separation Leads
to Complex Topologies.............................. 90
5.3.3 Extension to Random Boolean Networks ............... 93
5.3.4 Correlation-Based Rewiring in Neural Networks......... 96
Contents xj
5.4 Summary and Outlook......................................101
References.....................................................103
6 Self-Organization and Complex Networks ........................107
Guido Caldarelli and Diego Garlaschelli
6.1 Introduction...............................................107
6.2 Scale Invariance and Self-Organization........................109
6.2.1 Geometric Fractals..................................109
6.2.2 Self-Organized Criticality............................Ill
6.3 Complex Networks.........................................115
6.3.1 Network Properties..................................115
6.3.2 Network Models....................................116
6.4 A Self-Organized Network Model ............................122
6.4.1 Motivation.........................................123
6.4.2 Definition .........................................124
6.4.3 Analytical Solution..................................125
6.4.4 Particular Cases ....................................128
6.5 Conclusions...............................................132
References.....................................................133
7 Self-Organization of Network Structure in Coupled-Map Systems ... 137
Junji Ito and Kunihiko Kaneko
7.1 Introduction...............................................137
7.2 Adaptive Network of Logistic-Map Units......................138
7.2.1 Model Formulation..................................139
7.2.2 Unit Dynamics.....................................140
7.2.3 Connection Dynamics...............................I43
7.2.4 Network Structure ..................................I45
7.2.5 Dynamic Networks in the Desynchronized Phase.........147
7.3 Adaptive Network of Bursting Units ..........................I53
7.3.1 Model Formulation..................................l^3
7.3.2 Unit Dynamics.....................................I54
7.3.3 Connection Dynamics............................... 55
7.3.4 Mechanism of Structure Formation ....................158
7.4 Formation of Hierarchical Network Structure Triggered by
External Input............................................ ?
7.5 Summary and Discussion.................................... 6 J
References..................................................... -
8 Dynamical Optimization and Synchronization in Adaptive Complex
Networks......................................................165
Maoyin Chen and Jiirgen Kurths
8.1 Introduction...............................................i65
8.2 Phase Synchronization in the Kuramoto Model .................167
Contents
8.3 Complete Synchronization and Enhanced Synchronizability in
Adaptive Complex Networks................................ 175
8.3.1 Complete Synchronization in Adaptive Complex Networks 175
8.3.2 Enhanced Synchronizability in Adaptive Complex
Networks..........................................180
8.4 Conclusions...............................................186
References.....................................................187
Part III Contact Processes and Epidemiology on Adaptive Networks
9 Contact Processes and Moment Closure on Adaptive Networks......191
Anne-Ly Do and Thilo Gross
9.1 Introduction...............................................191
9.2 Opinion Formation - Theme and Variations....................193
9.2.1 Continuous Opinions................................194
9.2.2 Two-Valued Choice and Irreversible Discord............195
9.2.3 The Influence of Bounded Tolerance...................197
9.2.4 Asymmetric Insertion of Influence.....................199
9.2.5 Other Approaches...................................201
9.3 Epidemic Spreading and Moment Closure......................201
9.3.1 The Adaptive SIS Model.............................202
9.3.2 Other Approaches...................................206
9.4 Summary and Outlook......................................207
References.....................................................208
10 Noise Induced Dynamics in Adaptive Networks with Applications
to Epidemiology................................................209
Leah B. Shaw and Ira B. Schwartz
10.1 Introduction...............................................209
10.2 Model....................................................212
10.3 Bifurcation Structure.......................................214
10.4 Effect of Recovered Class on Fluctuations .....................216
10.5 Delayed Outbreaks.........................................221
10.6 Lifetime of the Endemic Steady State .........................222
10.7 Network Geometry.........................................223
10.8 Conclusions and Discussion .................................225
References.....................................................226
Part IV Social Games on Adaptive Networks
11 A Dynamic Model of Social Network Formation...................231
Brian Skyrms and Robin Pemantle
11.1 Introduction...............................................LD
Contents xijj
11.2 Making Friends: A Baseline Model of Uniform Reinforcement___234
11.2.1 Friends I: Asymmetric Weights .......................234
11.2.2 Friends II: Symmetrized Reinforcement................235
11.2.3 Analysis of Friends I and II...........................235
11.3 Making Enemies...........................................237
11.3.1 The Transfer Model.................................238
11.3.2 The Resistance Model...............................239
11.3.3 A Better Model?....................................240
11.4 Perturbations of the Models..................................240
11.4.1 Discounting the Past.................................240
11.4.2 Analysis of Discounting the Past......................241
11.4.3 Introduction of Noise................................242
11.4.4 Noise and Discounting...............................243
11.5 Reinforcement by Games of Nontrivial Strategy.................244
11.5.1 Rousseau s Stag Hunt ...............................244
11.5.2 Co-evolution of Structure and Strategy .................246
11.6 Conclusion................................................247
References.....................................................251
12 Evolutionary Games in Self-Organizing Populations ...............253
Arne Traulsen, Francisco C. Santos, and Jorge M. Pacheco
12.1 Evolutionary Game Dynamics ...............................253
12.2 Active Linking ............................................254
12.2.1 Linking Dynamics..................................255
12.2.2 Strategy Dynamics..................................256
12.2.3 Separation of Timescales.............................258
12.2.4 Effects of Active Linking.............................260
12.3 Individual Based Linking Dynamics ..........................261
12.3.1 Specification of the Linking Dynamics .................261
12.3.2 Numerical Results ..................................263
12.3.3 Graph Structures Under Individual Based Linking
Dynamics ......................................... *
12.4 Discussion................................................265
~Jf.fi.
References..................................................... DD
13 The Diplomat s Dilemma: Maximal Power for Minimal Effort
in Social Networks .......................................
Petter Holme and Gourab Ghoshal
1AQ
13.1 Introduction...............................................
13.2 Definition of the Model.....................................^
13.2.1 Preliminaries.......................................
13.2.2 Moves ............................................~ ~
13.2.3 Strategies..........................................
13.2.4 Strategy Updates and Stochastic Rewiring ..............-/4
Contents
13.2.5 The Entire Algorithm................................274
13.3 Numerical Results .........................................275
13.3.1 Time Evolution.....................................275
13.3.2 Example Networks..................................275
13.3.3 Effects of Strategies on the Network Topology...........277
13.3.4 Transition Probabilities..............................282
13.3.5 Dependence on System Size and Noise.................283
13.4 Discussion................................................284
References.....................................................287
Part V Graph-Rewriting-Based Approaches
14 Graph-Rewriting Automata as a Natural Extension of Cellular
Automata .....................................................291
Kohji Tomita, Haruhisa Kurokawa, and Satoshi Murata
14.1 Introduction...............................................291
14.2 Formulation...............................................292
14.2.1 Rules of Graph-Rewriting Automata...................293
14.2.2 Update Procedure...................................294
14.2.3 Simulation of Graph-Rewriting Automata...............295
14.2.4 Examples..........................................296
14.3 Rule Design by Hand-Coding................................297
14.3.1 Design of Self-replicating Turing Machine..............298
14.4 Rule Search by Evolutionary Computation.....................300
14.4.1 Evolutionary Computation ...........................300
14.4.2 Simulation Results..................................302
14.5 Exhaustive Trial ...........................................303
14.5.1 Rule Representation.................................304
14.5.2 Results............................................304
14.6 Conclusions...............................................307
References.....................................................3 °
15 Generative Network Automata: A Generalized Framework for
Modeling Adaptive Network Dynamics Using Graph Rewritings 311
Hiroki Sayama and Craig Laramee
15.1 Introduction...............................................3
15.2 About Graph Rewriting.....................................313
15.3 Definition of GNA.........................................3*4
15.4 Generality of GNA.........................................317
15.5 Computational Exploration of Possible Dynamics
of Simple Binary-State GNA................................ Ml
15.5.1 Assumptions.......................................317
15.5.2 Methods...........................................32°
Contents
15.5.3 Results............................................321
15.6 Conclusion................................................329
References.....................................................330
|
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| spelling | Adaptive networks theory, models and applications Thilo Gross ... eds. Dordrecht [u.a.] Springer 2009 XIX, 332 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Understanding complex systems Springer complexity New England Complex Systems Institute book series Netzwerk (DE-588)4171529-9 gnd rswk-swf Adaptives System (DE-588)4247928-9 gnd rswk-swf Komplexes System (DE-588)4114261-5 gnd rswk-swf Netzwerk (DE-588)4171529-9 s Komplexes System (DE-588)4114261-5 s Adaptives System (DE-588)4247928-9 s DE-604 Gross, Thilo 1976- (DE-588)129590363 edt HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018715556&sequence=000004&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
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| title | Adaptive networks theory, models and applications |
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