Social Self-Organization

1. Front Matter

   Pages i-xi

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2. Modeling of Socio-Economic Systems

   • Dirk Helbing

   Pages 1-24

3. Agent-Based Modeling

   • Dirk Helbing

   Pages 25-70

4. Self-organization in Pedestrian Crowds

   • Dirk Helbing

   Pages 71-99

5. Opinion Formation

   • Dirk Helbing

   Pages 101-114

6. Spatial Self-organization Through Success-Driven Mobility

   • Dirk Helbing

   Pages 115-130

7. Cooperation in Social Dilemmas

   • Dirk Helbing

   Pages 131-138

8. Co-evolution of Social Behavior and Spatial Organization

   • Dirk Helbing

   Pages 139-151

9. Evolution of Moral Behavior

   • Dirk Helbing

   Pages 153-167

10. Coordination and Competitive Innovation Spreading in Social Networks

    • Dirk Helbing

    Pages 169-184

11. Heterogeneous Populations: Coexistence, Integration, or Conflict

    • Dirk Helbing

    Pages 185-199

12. Social Experiments and Computing

    • Dirk Helbing

    Pages 201-209

13. Learning of Coordinated Behavior

    • Dirk Helbing

    Pages 211-237

14. Response to Information

    • Dirk Helbing

    Pages 239-259

15. Systemic Risks in Society and Economics

    • Dirk Helbing

    Pages 261-284

16. Managing Complexity

    • Dirk Helbing

    Pages 285-299

17. Challenges in Economics

    • Dirk Helbing

    Pages 301-329

18. Back Matter

    Pages 331-340

    PDF

What are the principles that keep our society together? This question is even more difficult to answer than the long-standing question, what are the forces that keep our world together. However, the social challenges of humanity in the 21st century ranging from the financial crises to the impacts of globalization, require us to make fast progress in our understanding of how society works, and how our future can be managed in a resilient and sustainable way. This book can present only a few very first steps towards this ambitious goal. However, based on simple models of social interactions, one can already gain some surprising insights into the social, ``macro-level'' outcomes and dynamics that is implied by individual, ``micro-level'' interactions. Depending on the nature of these interactions, they may imply the spontaneous formation of social conventions or the birth of social cooperation, but also their sudden breakdown. This can end in deadly crowd disasters or tragedies of the commons (such as financial crises or environmental destruction). Furthermore, we demonstrate that classical modeling approaches (such as representative agent models) do not provide a sufficient understanding of the self-organization in social systems resulting from individual interactions. The consideration of randomness, spatial or network interdependencies, and nonlinear feedback effects turns out to be crucial to get fundamental insights into how social patterns and dynamics emerge. Given the explanation of sometimes counter-intuitive phenomena resulting from these features and their combination, our evolutionary modeling approach appears to be powerful and insightful. The chapters of this book range from a discussion of the modeling strategy for socio-economic systems over experimental issues up the right way of doing agent-based modeling.  We furthermore discuss applications ranging from pedestrian and crowd dynamics over opinion formation, coordination, and cooperationup to conflict, and also address the response to information, issues of systemic risks in society and economics, and new approaches to manage complexity in socio-economic systems. Selected parts of this book had been previously published in peer reviewed journals.

• Agent Based Modelling
• Behaviour Social Networks
• Computational Social Science
• Emergent Social Beahiour
• Innovation Spreading Networks
• Managing Complexity
• Opinion Formation Social System
• Risks Society Economics
• Self Organization Crowds
• Socio-economic Systems

From the reviews:

“This volume is a collection of models whose aim is not only to better explain a variety of phenomena in the social, cultural and economic realms using agent-based models, but also to manage these complex phenomena. … I recommend this as an important addition to the growing work on both the theoretical and practical world of agent-based simulation modelling in the social sciences.” (John Bragin, Journal of Artificial Societies and Social Simulation, April, 2013)

• Lehrstuhl Soziologie, CLU E1, ETH Zürich, Zürich, Switzerland

  Dirk Helbing

Dirk Helbing,
ETH Zürich

Chair of Sociology Dept., Theoretical physicist, Worldwide leading scientist in computational social sciences and econophysics/complexity research.

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