Complexity and the Human Experience: Modeling Complexity in the Humanities and Social Sciences

301 Pages·2014·5.049 MB·English

by  Paul A. Youngman, Mirsad Hadzikadic

Complexity and
the Human Experience

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Complexity and
the Human Experience
Modeling Complexity in the Humanities and Social Sciences
edited by
Paul A. Youngman | Mirsad Hadzikadic
editors
PrebenMaegaard
AnnaKrenz
WolfgangPalz
The Rise of Modern Wind Energy
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Contents
Preface
Introduction: Computer Modeling in Humanities and xi
Social Sciences 1
Paul A. Youngman and Mirsad Hadzikadic
Part 1: Complex Adaptive Systems in the Humanities
1. Philosophical Analysis in Modeling Polarization: Notes from
Work in Progress 11
Patrick Grim, Aaron Bramson, Daniel J. Singer, Steven Fisher,
Carissa Flocken, and William Berger
1.1 Introduction 12
1.2 Computational Modeling and Philosophical Analysis 13
1.3 Understanding Polarization: Initial Motivations 14
1.4 The First Models 17
1.5 Conceptual Questions from Computational Models 18
1.6 Exploring the Impact of Alternatives 20
1.7 Philosophical Analysis in Computational Modeling:
The Case of Polarization 23
1.8 First Results and Work in Progress 29
2. Overcoming Moral Hypocrisy in a Virtual Society 39
1.9 Conclusion 34
Markus Christen
2.1 Introduction 39
2.2 The Moral Hypocrisy Model 41
2.2.1 Conceptualization of Moral Hypocrisy 41
2.2.2 Model and Social Strategies Implementation 42
2.3 Paradigmatic Scenarios 45
2.4 Defining a Measure for Population Diversity 48
2.5 Results 48
vi Contents
2.5.1 Scenario Parameters Determine Population
Distributions 49
2.5.2 Strategy Rankings and Conflicting Effects
of Interventions 50
2.5.3 Strategy Effects Attributed to Four “Moral
Worlds” 51
2.5.4 Scenario-Diversity Overcomes Moral
Hypocrisy 52
3. Evolving Games and the Social Contract 61
2.6 Discussion and Conclusion 56
Rory Smead
3.1 Introduction 61
3.2 Evolution of Behavior in Games 63
3.3 Games of Incomplete Information 65
3.4 Evolution with Incomplete Information 66
3.5 Evolution of the Game 67
3.6 Other Models of Evolving Games 70
3.7 Social Contracts with Evolving Games 71
3.7.1 Cooperation with Environmental
Degradation 71
3.7.2 Cultural Shifts: Increasing the Value
of Cooperation 73
3.7.3 Fair Division in an Evolving Game 76
4. Character Networks for Narrative Generation: Structural
3.8 Conclusion 77
Balance Theory and the Emergence of Proto-Narratives 81
Graham Alexander Sack
4.1 Introduction 82
4.2 From Narratives to Networks 85
4.3 From Networks to Narratives 88
4.3.1 Background: Structural Balance Model 88
4.3.2 Model Implementation 90
4.4 Conclusion 100
Contents vii
5. Modeling the Communications Circuit: An Agent-Based
Approach to Reading in “N-Dimensions” 105
Jeremy Throne
5.1 Introduction 106
5.2 Book History 108
5.2.1 The Communications Circuit 109
5.3 The Communications Circuit: An Agent-Based
Model 109
5.4 Limitations 111
5.5 Applications 114
5.6 A Model in Motion: Demonstration and Results 115
6. The Potential of Agent-Based Modelling for Historical
5.7 Conclusions 118
Research 121
Marten Düring
6.1 Introduction 122
6.2 Computational Methods and Counterfactual
Thinking in History 124
6.3 Agent-Based Modelling of Historical Facts 125
6.4 Case Studies 127
6.4.1 The Disappearance of the Anasazi 127
6.4.2 The Battle of Trafalgar 128
6.4.3 The Flu in Manitoba 130
6.5 PDaisrctu 2ss:i Cono mplex Adaptive Systems in the 131
Social Sciences
7. Complexity Theory and Political Change: Talcott Parsons
Occupies Wall Street 141
Martin Zwick
7.1 Introduction 141
7.2 Parsons’ Model of Societal Systems 143
7.3 Flaws of Differentiation 148
viii Contents
7.4 Digression 152
7.5 Fixing the Flaws 153
8. China’s Complex Policy Network 161
7.6 Summary 158
Jerome Tan Sibayan
8.1 Introduction 161
8.2 China’s Central Committee 163
8.3 The Chinese Conception of Guanxi 164
8.3.1 Educational Level as Guanxi 165
8.3.2 Military Experience as Guanxi 165
8.3.3 Provincial Origin as Guanxi 165
8.3.4 Special Connections 166
8.4 Recreating the Network 167
8.4.1 Sources, Interpretation, and Coding of Data 167
8.5 Five Characteristics of a Complex System 168
8.5.1 A Scale-Free Network 168
8.5.2 A Small World After All? 169
8.5.3 Emergent Order 170
8.5.4 Emergent Functionality 172
8.5.5 Resilience of Guanxi Networks 176
9. Convergence versus Emergence of Youth Extremism:
8.6 What a Complex Policy Network May Mean 178
An Agent-Based Model of the Arab Spring 183
Dana Downey
9.1 Introduction 183
9.2 The Effect of the Youth Bulge on Collective Action 185
9.3 Modeling the Youth Bulge in an Agent Population 187
9.3.1 Model Dynamics 192
9.3.2 Results 193
9.4 Referencing Collective Action Theory and Convergent
Theories in Agent-Based Modeling 196
9.4.1 Referencing Further Factors for Future
Modeling 198
9.5 Conclusion 199
Contents ix
10. Complexity of Structure in Electronic Medical Record
Systems 203
Russell S. Gonnering, Gregory S. H. Ogawa, Sven-Erik Bursell,
and Mark B. Horton
10.1 Introduction 204
10.2 Methods 208
10.3 Results 209
11. 1A0d.a4p tDatisiocnu sosfi oFono dways and Indicators of Malnutrition: 213
Philippines as a Case Study 221
Amanda L. Andrei
11.1 Introduction 222
11.2 Method of Analysis 223
11.3 Results 225
11.4 Discussion 231
11.5 Future Research Possibilities 236
12. Exploiting the Synergy between the Micro, Meso, and
11.6 Summary 238
Macro Levels in a Complex System: Bringing to Life an
Ancient Urban Center 241
Thaer W. Jayyousi and Robert G. Reynolds
12.1 Introduction 242
12.2 Cultural Algorithms 243
12.3 The Emergence of Monte Albán: An Example
Approach 244
12.3.1 City Morphologies: Hypothetical Models
of Urban Growth 244
12.3.2 The Emergence of Monte Albán 245
12.3.3 The Monte Albán Dataset 247
12.4 Exploiting Multiple Spatial Levels: Macro, Meso,
and Micro 249
12.4.1 Introduction 249
12.4.2 Macro Level (The City) 251
12.4.3 Meso Level (The Barrios) 256
12.4.4 Micro Level (The Terraces) 257