Hostname: page-component-78c5997874-t5tsf Total loading time: 0 Render date: 2024-11-19T07:20:42.720Z Has data issue: false hasContentIssue false
  • English
  • Français

Establishing social cooperation: The role of hubs and community structure

Published online by Cambridge University Press:  29 May 2018

BARRY COOPER ,
ANDREW E. M. LEWIS-PYE ,
ANGSHENG LI ,
YICHENG PAN  and
XI YONG
BARRY COOPER
Affiliation:
Department of Mathematics, University of Leeds, Leeds LS2 9JT, UK (e-mail: [email protected])
ANDREW E. M. LEWIS-PYE
Affiliation:
Department of Mathematics, London School of Economics and Political Science, London WC2A 2AE, UK (e-mail: [email protected])
ANGSHENG LI
Affiliation:
State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing 100190, P. R. China (e-mail: [email protected], [email protected])
YICHENG PAN
Affiliation:
State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing 100190, P. R. China (e-mail: [email protected], [email protected])
XI YONG
Affiliation:
State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing 100190, P. R. China University of the Chinese Academy of Sciences, Beijing 100190, P. R. China (e-mail: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Prisoner's Dilemma (PD) games have become a well-established paradigm for studying the mechanisms by which cooperative behavior may evolve in societies consisting of selfish individuals. Recent research has focused on the effect of spatial and connectivity structure in promoting the emergence of cooperation in scenarios where individuals play games with their neighbors, using simple “memoryless” rules to decide their choice of strategy in repeated games. While heterogeneity and structural features such as clustering have been seen to lead to reasonable levels of cooperation in very restricted settings, no conditions on network structure have been established, which robustly ensure the emergence of cooperation in a manner that is not overly sensitive to parameters such as network size, average degree, or the initial proportion of cooperating individuals. Here, we consider a natural random network model, with parameters that allow us to vary the level of “community” structure in the network, as well as the number of high degree hub nodes. We investigate the effect of varying these structural features and show that, for appropriate choices of these parameters, cooperative behavior does now emerge in a truly robust fashion and to a previously unprecedented degree. The implication is that cooperation (as modelled here by PD games) can become the social norm in societal structures divided into smaller communities, and in which hub nodes provide the majority of inter-community connections.

Keywords

cooperative behaviourPrisoner's Dilemmarepeated gameshubscommunitycomputer sciencesociology
Type
Research Article
Information
Network Science , Volume 6 , Issue 2 , June 2018 , pp. 251 - 264
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Axelrod, R. (1980a). Effective choice in the Prisoner's Dilemma. Journal of Conflict Resolution, 24, 3–25.CrossRefGoogle Scholar
Axelrod, R. (1980b). More effective choice in the Prisoner's Dilemma. Journal of Conflict Resolution, 24, 379–403.CrossRefGoogle Scholar
Bell, G. (2008). Selection: The mechanism of evolution. Oxford: Oxford University Press.Google Scholar
Barabási, A. L. (2009). Scale-free networks: a decade and beyond. Science, 325(5939), 412–413.CrossRefGoogle ScholarPubMed
Barabási, A. L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509–512.CrossRefGoogle ScholarPubMed
Darwin, C. (1859). On the origin of species by means of natural selection. London: John Murray.Google Scholar
Dawkins, R. (2006). The selfish gene (30th anniversary ed.). Oxford, UK: Oxford University Press.Google Scholar
Gómez-Gardenes, J., Campillo, M., Floría, L. M., & Moreno, Y. (2007). Dynamical organization of cooperation in complex topologies. Physical Review Letters, 98. doi: 10.1103/PhysRevLett.98.108103.CrossRefGoogle ScholarPubMed
Huberman, B., & Glance, N. (1993). Evolutionary games and computer simulations. Proceedings of the National Academy of Sciences of the United States of America, 90, 7716–7718.CrossRefGoogle ScholarPubMed
Li, A., & Pan, Y. (2015). A theory of network security: Principles of natural selection and combinatorics. Internet Mathematics, 12, 145–204.CrossRefGoogle Scholar
Lieberman, E., Hauert, C., & Nowak, M. A. (2005). Evolutionary dynamics on graphs. Nature, 433, 312–316.CrossRefGoogle Scholar
Newman, M. (2010). Networks: An introduction. New York, NY, USA: Oxford University Press.CrossRefGoogle Scholar
Nowak, M. A., & May, R. M. (1992). Evolutionary games and spatial chaos. Nature, 359, 826–829.CrossRefGoogle Scholar
Pacheco, J. M., & Santos, F. C. (2005). Network dependence of the dilemmas of cooperation. AIP Conference Proceedings, 776, 90–100.CrossRefGoogle Scholar
Pennisi, E. (2005). How did cooperative behaviour evolve. Science, 309, 93–93.CrossRefGoogle ScholarPubMed
Roca, C. P., Cuesta, J. A., & Sánchez, A. (2009). Evolutionary game theory: Temporal and spatial effects beyond replicator dynamics. Physics of Life Reviews, 6 (4), 208–249.CrossRefGoogle ScholarPubMed
Santos, F. C., & Pacheco, J. M. (2005). Scale-free networks provide a unifying framework for the emergence of cooperation. Physical Review Letters, 95 (9), 98–104.CrossRefGoogle ScholarPubMed
Santos, F. C., & Pacheco, J. M. (2006). A new route to the evolution of cooperation. European Society for Evolutionary Biology, 19, 726–733.CrossRefGoogle ScholarPubMed
Santos, F. C., Pacheco, J. M., & Lenaerts, T. (2006a). Evolutionary dynamics of social dilemmas in structured heterogeneous populations. Proceedings of the National Academy of Sciences of the United States of America, 103 (9): 3490–3494.CrossRefGoogle ScholarPubMed
Santos, F. C., Pacheco, J. M., & Lenaerts, T. (2006b). Cooperation prevails when individuals adjust their social ties. PLoS Computational Biology, 2 (10): e140.CrossRefGoogle ScholarPubMed
Smith, J. M. (1964). Group selection and kin selection. Nature, 201(4924), 1145–1147.CrossRefGoogle Scholar
Smith, J. M. (1982). Evolution and the theory of games. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Szabó, G., & Fáth, G. (2007). Evolutionary games on graphs. Physics Reports, 446, 97–216.CrossRefGoogle Scholar
Szabó, G., & Tőke, C. (1998). Evolutionary Prisoner's Dilemma game on a square lattice. Physical Review E, 58, 69.CrossRefGoogle Scholar
Traulsen, A., Semmann, D., Sommerfeld, R. D., Krambeck, H.-J., & Milinski, M. (2010). Human strategy updating in evolutionary games. Proceedings of the National Academy of Sciences of the United States of America, 107 (7), 2962–2966.CrossRefGoogle ScholarPubMed
Vukov, J., Szabó, G., & Szolnoki, A. (2008). Evolutionary Prisoner's Dilemma game on Newman-Watts networks. Physical Review E, 77. doi: 10.1103/PhysRevE.77.026109.CrossRefGoogle ScholarPubMed
Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of small world networks. Nature, 393, 440–442.CrossRefGoogle ScholarPubMed