A thorough look at how societies can use cultural algorithms to understand human social evolution
For those working in computational intelligence, developing an understanding of how cultural algorithms and social intelligence form the essential framework for the evolution of human social interaction is essential. This book, Cultural Algorithms: Tools to Model Complex Dynamic Social Systems, is the foundation of that study. It showcases how we can use cultural algorithms to organize social structures and develop socio-political systems that work.
For such a vast topic, the text covers everything from the history of the development of cultural algorithms and the basic framework with which it was organized. Readers will also learn how other nature-inspired algorithms can be expressed and how to use social metrics to assess the performance of various algorithms.
In addition to these topics, the book covers topics including:
- The CAT system including the Repast Simphony System and CAT Sample Runs
- How to problem solve using social networks in cultural algorithms with auctions
- Understanding Common Value Action to enhance Social Knowledge Distribution Systems
- Case studies on team formations
- An exploration of virtual worlds using cultural algorithms
For industry professionals or new students, Cultural Algorithms provides an impactful and thorough look at both social intelligence and how human social evolution translates into the modern world.
Table of Contents:
List of Contributors ix
About the Companion Website xi
1 System Design Using Cultural Algorithms 1
Robert G. Reynolds
Introduction 1
The Cultural Engine 4
Outline of the Book: Cultural Learning in Dynamic Environments 6
References 10
2 The Cultural Algorithm Toolkit System 11
Thomas Palazzolo
CAT Overview 11
Downloading and Running CAT 14
The Repast Simphony System 15
Knowledge Sources 15
Fitness Functions 18
ConesWorld 19
The Logistics Function 23
CAT Sample Runs: ConesWorld 24
CAT Sample Runs: Other Problems 32
Reference 34
3 Social Learning in Cultural Algorithms with Auctions 35
Robert G. Reynolds and Leonard Kinnaird-Heether
Introduction 35
Cultural Algorithms 37
Subcultured Multi-Layered, Deep Heterogeneous Networks 40
Auction Mechanisms 42
The Cultural Engine 45
ConesWorld 47
Experimental Framework 50
Results 50
Conclusions 54
References 55
4 Using Common Value Auction in Cultural Algorithm to Enhance Robustness and Resilience of Social Knowledge Distribution Systems 57
Anas AL-Tirawi and Robert G. Reynolds
Cultural Algorithms 57
Common Value Auction 62
ConesWorld 64
Dynamic Experimental Framework 66
Results 67
Conclusions and Future Work 73
References 73
5 Optimizing AI Pipelines: A Game-Theoretic Cultural Algorithms Approach 75
Faisal Waris and Robert G. Reynolds
Introduction 75
Overview of Cultural Algorithms 77
CA Knowledge Distribution Mechanisms 78
Primer on Game Theory 80
Game- Theoretic Knowledge Distribution 81
Continuous-Action Iterated Prisoner’s Dilemma 82
Test Results: Benchmark Problem 89
Test Results: Computer Vision Pipeline 92
Conclusions 95
References 96
6 Cultural Algorithms for Social Network Analysis: Case Studies in Team Formation 98
Kalyani Selvarajah, Ziad Kobti, and Mehdi Kargar
Introduction 98
Application of Social Network 99
Forming Successful Teams 99
Formulating TFP 100
Communication Cost 101
Personnel Cost 101
Distance Cost 102
Workload Balance 102
Why Artificial Intelligence? 103
Cultural Algorithms 103
Forming Teams in Coauthorship Network 104
Individual Representation 105
Fitness Function 107
Belief Space 107
Dataset and Observations 108
Skill Frequency 108
Forming Teams in Health-care Network 108
Individual Representation 113
Fitness Function 114
Dataset and Observation 115
Summary and Conclusion 117
References 117
7 Evolving Emergent Team Strategies in Robotic Soccer using Enhanced Cultural Algorithms 119
Mostafa Z. Ali, Mohammad I. Daoud, Rami Alazrai, and Robert G. Reynolds
Introduction 119
Related Work 121
The 2D Soccer Simulation Test Bed 122
Evolution of Team Strategies via Cultural Algorithm 124
Experiments and Analysis of Results 132
Conclusion 138
References 139
8 The Use of Cultural Algorithms to Learn the Impact of Climate on Local Fishing Behavior in Cerro Azul, Peru 143
Khalid Kattan, Robert G. Reynolds, and Samuel Dustin Stanley
Introduction 143
An Overview of the Cerro Azul Fishing Dataset 143
Data Mining at the Macro, Meso, and Micro Levels 148
Cultural Algorithms and Multiobjective Optimization 149
The Artisanal Fishing Model 153
The Experimental Results 159
Statistical Validation 163
Conclusions and Future Work 166
References 167
9 CAPSO: A Parallelized Multiobjective Cultural Algorithm Particle Swarm Optimizer 169
Samuel Dustin Stanley, Khalid Kattan, and Robert G. Reynolds
Introduction 169
Multiobjective Optimization 170
Cultural Algorithms 171
CAPSO Knowledge Structures 174
Tracking Knowledge Source Progress (Other than Topographic) 176
CAPSO Algorithm Pseudocode 177
Multiple Runs 180
Comparison of Benchmark Problems 180
Overall Summary of Results 192
Other Applications 192
References 193
10 Exploring Virtual Worlds with Cultural Algorithms: Ancient Alpena–Amberley Land Bridge 195
Thomas Palazzolo, Robert G. Reynolds, and Samuel Dustin Stanley
Archaeological Challenges 195
Generalized Framework 198
The Land Bridge Hypothesis 199
Origin and Form 204
Putting Data to Work 205
Pathfinding and Planning 215
Identifying Good Locations: The Hotspot Finder 218
Cultural Algorithms 222
Cultural Algorithm Mechanisms 225
The Composition of the Belief Space 226
Future Work 227
Path Planning Strategy 227
Local Tactics 229
Detailed Locational Information 230
Extending the CA 231
Human Presence in the Virtual World 234
Increasing the Complexity 235
Updated Path-Planning Results in Unity 236
The Fully Rendered Land Bridge 237
Pathfinder Mechanisms 239
Results 245
Conclusions 254
References 255
Index 259
About the Author :
DR. ROBERT G. REYNOLDS is a Professor of Computer Science at Wayne State University and a Visiting Research Scientist at the University of Michigan's Museum of Anthropology. In addition to serving as the Computational Intelligence Representative to the IEEE USA Research and Development Committee, he has also been an Associate Editor for eight Intelligent System and IEEE journals.
