Evolutionary dynamics of cooperation in a population with probabilistic corrupt enforcers and violators

Author:

Liu Linjie1,Chen Xiaojie1,Szolnoki Attila2

Affiliation:

1. School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China

2. Institute of Technical Physics and Materials Science, Centre for Energy Research, Hungarian Academy of Sciences, P. O. Box 49, H-1525 Budapest, Hungary

Abstract

Pro-social punishment is a key driver of harmonious and stable society. However, this institution is vulnerable to corruption since law-violators can avoid sanctioning by paying bribes to corrupt law-enforcers. Consequently, to understand how altruistic behavior survives in a corrupt environment is an open question. To reveal potential explanations here, we introduce corrupt enforcers and violators into the public goods game with pool punishment, and assume that punishers, as corrupt enforcers, may select defectors probabilistically to take a bribe from, and meanwhile defectors, as corrupt violators, may select punishers stochastically to be corrupted. By means of mathematical analysis, we aim to study the necessary conditions for the evolution of cooperation in such corrupt environment. We find that cooperation can be maintained in the population in two distinct ways. First, cooperators, defectors, and punishers can coexist by all keeping a steady fraction of the population. Second, these three strategies can form a cyclic dominance that resembles a rock-scissors-paper cycle or a heteroclinic cycle. We theoretically identify conditions when the competing strategies coexist in a stationary way or they dominate each other in a cyclic way. These predictions are confirmed numerically.

Funder

National Natural Science Foundation of China

Hungarian National Research Fund

Publisher

World Scientific Pub Co Pte Lt

Subject

Applied Mathematics,Modelling and Simulation

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