Abstract
Cooperation is of utmost importance to society, but is often challenged by individual self-interests. While game theory has studied this problem extensively, there is little work on interactions within and across groups with heterogeneous preferences. Yet, interactions between people with incompatible interests often yield conflict, since behavior that is considered cooperative by one population might be perceived as non-cooperative by another. To understand the outcome of such competitive interactions, we study game-dynamical replicator equations for multiple populations with incompatible preferences and different power to reveal, for example, what mechanisms can foster the evolution of behavioral norms? When does cooperation fail, leading to conflict or even to revolutions? What incentives are needed to reach peaceful agreements? Our quantitative analysis reveals some striking results, significant for society, law, and economics.
The content of this chapter has some overlap with the following two papers, which should be cited instead: D. Helbing and A. Johansson, Evolutionary dynamics of populations with conflicting interactions: Classification and analytical treatment considering asymmetry and power. Physical Review E 81, 016112 (2010); D. Helbing and A. Johansson, Cooperation, norms, and revolutions: A unified game-theoretical approach. PLoS ONE 5(10): e12530.
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Acknowledgements
The authors would like to thank for partial support by the EU Project QLectives and the ETH Competence Center “Coping with Crises in Complex Socio-Economic Systems” (CCSS) through ETH Research Grant CH1-01 08-2. They are grateful to Thomas Chadefaux, Ryan Murphy, Carlos P. Roca, Stefan Bechtold, Sergi Lozano, Heiko Rauhut, Wenjian Yu and further colleagues for valuable comments and to Sergi Lozano for drawing Fig. 10.1. D.H. thanks Thomas Voss for his insightful seminar on social norms.
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Helbing, D. (2012). Heterogeneous Populations: Coexistence, Integration, or Conflict. In: Helbing, D. (eds) Social Self-Organization. Understanding Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24004-1_10
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