Data from: Evolution of conditional cooperation in public good games
Cite this dataset
Battu, Balaraju; Srinivasan, Narayanan (2020). Data from: Evolution of conditional cooperation in public good games [Dataset]. Dryad. https://doi.org/10.5061/dryad.f7m0cfxrc
It is observed that in a repeated public good game with same individuals, free riding by a few individuals in the initial rounds triggers free riding by others in the subsequent rounds. It is presumed that individuals tend to imitate social behaviour of successful or relatively high payoff individuals, irrespective of how the payoffs were obtained. However, humans are concerned about how the payoffs were obtained, such as whether the payoffs were obtained by cheating or good behaviour. Individuals are willing to incur certain cost in order to improve group benefits and these individuals gain prestige. In human societies individuals tend to imitate social behaviour of high prestige agents. We propose that when agents are aware of other agents’ payoffs scores and their prestige, perhaps agents are more likely to imitate social behaviour of high prestige and high payoff agents. We introduce, population level affinity parameters such as affinity towards payoff and affinity towards prestige of role models. We show that, for certain affinity parameters, high levels of cooperation are established in a population consisting of heterogeneous conditional co-operators, when agents imitate social behaviour of high prestige and high payoff agents. The proposed model provides insights into why value-based societies are more successful than competitive societies in establishing cooperation.
- The function “ PGG_MAIN.m” is a Matlab file implementation of the model.
- The program file, “PGG_MAIN_RUN.m” is for creating data using PGG_MAIN function.
- The program file, “randnlimt.m” is for creating mutations and used by PGG_MAIN.m.
- The data and plotting program, “data_figures_RSOS.m” is available in the folder PGG