Evolutionary Games with Payoff Perturbations

Past decades have seen numerous studies about evolutionary games on networks, and most of them have been based on the assumption of exact payoff information. However, in both natural and engineering systems, interactions between agents are often subject to various perturbations, arising from environmental change and the disturbance of communications, and the loss of information. These often lead to perturbations in the payoff one derives. Here we propose a model of evolutionary games with payoff perturbations in networked systems and aim to investigate the evolutionary dynamics in the presence of perturbed payoffs. We provide an analytical condition to predict the strategy evolution. Surprisingly, compared with the evolutionary outcomes with exact payoffs, payoff perturbations relax the condition for the establishment of collective cooperation. Our work suggests that the perturbations occurring in interactions can be of great importance in establishing collective intelligence.