Details

Cultural Algorithms

Tools to Model Complex Dynamic Social Systems
IEEE Press Series on Computational Intelligence 1. Aufl.

von: Robert G. Reynolds
116,99 €
Verlag:	Wiley
Format:	EPUB
Veröffentl.:	18.11.2020
ISBN/EAN:	9781119403104
Sprache:	englisch
Anzahl Seiten:	288

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Beschreibungen

Titelbeschreibung

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: <ul> <li>The CAT system including the Repast Simphony System and CAT Sample Runs</li> <li>How to problem solve using social networks in cultural algorithms with auctions</li> <li>Understanding Common Value Action to enhance Social Knowledge Distribution Systems</li> <li>Case studies on team formations</li> <li>An exploration of virtual worlds using cultural algorithms</li> </ul> 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.

Inhaltsverzeichnis

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

Autorenportrait

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.

Back cover copy

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 collective intelligence emerges from the interaction of human agents over time 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 for sustainable learning in dynamic environments. For such a vast topic, the text covers everything from the history of the development of cultural algorithms from the standpoint of Agent-Based modeling and Complex Systems. Readers will also learn how other nature-inspired algorithms can be expressed in a cultural context and how to use social metrics to assess the performance of various cultural algorithms. In addition to these topics, the book covers topics including: <ul> <li>An overview of the Cultural Algorithms Toolkit (CAT) for prototyping Cultural Algorithms along with CAT Sample Runs</li> <li>Problem solving using social networks in cultural algorithms with auctions</li> <li>Multi-layered deep social learning with subcultures</li> <li>Use of Formal Game Theory to enhance Social Knowledge Distributio in Cultural Algorithms</li> <li>Cultural Learning as a Thermodynamic Process-the Cultural Engine as a vehicle for sustainable learning</li> <li>Multi-Objective problem solving in Cultural Algorithms</li> <li>Case studies on team formations</li> <li>An exploration of virtual worlds using Cultural Algorithms</li> </ul> For industry professionals or new students interested in the foundation of social intelligence, Cultural Algorithms provides an impactful and thorough look how collective intelligence can emerge over time and how human social evolution translates into the modern world.