How the initial level of visibility and limited resource affect the evolution of cooperation

This work sheds important light on how the initial level of visibility and limited resource might affect the evolution of the players’ strategies under different network structure. We perform the prisoner’s dilemma game in the lattice network and the scale-free network, the simulation results indicate that the average density of death in lattice network decreases with the increases of the initial proportion of visibility. However, the contrary phenomenon is observed in the scale-free network. Further results reflect that the individuals’ payoff in lattice network is significantly larger than the one in the scale-free network. In the lattice network, the visibility individuals could earn much more than the invisibility one. However, the difference is not apparent in the scale-free network. We also find that a high Successful-Defection-Payoff (SDB) and a rich natural environment have relatively larger deleterious cooperation effects. A high SDB is beneficial to raising the level of visibility in the heterogeneous network, however, that has adverse visibility consequences in homogeneous network. Our result reveals that players are more likely to cooperate voluntarily under homogeneous network structure.

[1]  N. Christakis,et al.  Human behavior under economic inequality shapes inequality , 2015, Proceedings of the National Academy of Sciences.

[2]  M. Perc,et al.  Social diversity and promotion of cooperation in the spatial prisoner's dilemma game. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[3]  John H. Kagel,et al.  Personality and cooperation in finitely repeated prisoner’s dilemma games , 2014 .

[4]  Yi Tao,et al.  The replicator equation and other game dynamics , 2014, Proceedings of the National Academy of Sciences.

[5]  Lin Wang,et al.  Evolutionary games on multilayer networks: a colloquium , 2015, The European Physical Journal B.

[6]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[7]  Matjaz Perc,et al.  Aspiring to the Fittest and Promotion of Cooperation in the Prisoner's Dilemma Game , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[8]  A. Weiss,et al.  Distinct phases in the positive selection of CD8+ T cells distinguished by intrathymic migration and T-cell receptor signaling patterns , 2014, Proceedings of the National Academy of Sciences.

[9]  Peng Lu,et al.  Social Stratification and Cooperative Behavior in Spatial Prisoners' Dilemma Games , 2015, PloS one.

[10]  Zhi-Xi Wu,et al.  Spatial prisoner's dilemma game with volunteering in Newman-Watts small-world networks. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[11]  G. Szabó,et al.  Evolutionary games on graphs , 2006, cond-mat/0607344.

[12]  Soon-Hyung Yook,et al.  Percolation in spatial evolutionary prisoner's dilemma game on two-dimensional lattices. , 2015, Physical review. E, Statistical, nonlinear, and soft matter physics.

[13]  Simon J. Godsill,et al.  On sequential Monte Carlo sampling methods for Bayesian filtering , 2000, Stat. Comput..

[14]  Martijn J. van den Assem,et al.  Split or Steal? Cooperative Behavior When the Stakes Are Large , 2011, Manag. Sci..

[15]  G. Szabó,et al.  Phase diagrams for an evolutionary prisoner's dilemma game on two-dimensional lattices. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[16]  B. Muthén,et al.  Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study , 2007 .

[17]  Bing-Hong Wang,et al.  Braess's Paradox in Epidemic Game: Better Condition Results in Less Payoff , 2013, Scientific Reports.

[18]  Alexander J. Stewart,et al.  Collapse of cooperation in evolving games , 2014, Proceedings of the National Academy of Sciences.

[19]  Mei Sun,et al.  Can memory and conformism resolve the vaccination dilemma , 2014 .

[20]  Salahuddin M. Kamal,et al.  An evolutionary inspection game with labour unions on small-world networks , 2015, Scientific Reports.

[21]  G. Szabó,et al.  Cooperation enhanced by inhomogeneous activity of teaching for evolutionary Prisoner's Dilemma games , 2006, q-bio/0610001.

[22]  C. Hauert,et al.  Models of cooperation based on the Prisoner's Dilemma and the Snowdrift game , 2005 .

[23]  Matjaz Perc,et al.  Evolution of public cooperation in a monitored society with implicated punishment and within-group enforcement , 2015, Scientific Reports.

[24]  Angsheng Li,et al.  Entanglement Guarantees Emergence of Cooperation in Quantum Prisoner's Dilemma Games on Networks , 2014, Scientific Reports.

[25]  David G. Rand,et al.  Inequality and visibility of wealth in experimental social networks , 2015, Nature.

[26]  A. Sanchez,et al.  Co-evolution of strategies and update rules in the prisoner's dilemma game on complex networks , 2010, 1007.3626.

[27]  Attila Szolnoki,et al.  Competition and cooperation among different punishing strategies in the spatial public goods game , 2015, Physical review. E, Statistical, nonlinear, and soft matter physics.

[28]  Dong Hao,et al.  Diversity of timescale promotes the maintenance of extortioners in a spatial prisoner’s dilemma game , 2015 .

[29]  Xiaofeng Wang,et al.  Beyond pairwise strategy updating in the prisoner's dilemma game , 2012, Scientific Reports.

[30]  Pradeep Bhardwaj,et al.  Cooperation in Games with Forgetfulness , 2011, Manag. Sci..

[31]  Mei Sun,et al.  An evolutionary vaccination game in the modified activity driven network by considering the closeness , 2015, Physica A: Statistical Mechanics and its Applications.

[32]  M. Nowak Five Rules for the Evolution of Cooperation , 2006, Science.

[33]  Attila Szolnoki,et al.  Coevolutionary Games - A Mini Review , 2009, Biosyst..