Evolution of cooperation driven by sampling reward

Xiao, Jiafeng and Liu, Linjie and Chen, Xiaojie and Szolnoki, Attila (2023) Evolution of cooperation driven by sampling reward. JOURNAL OF PHYSICS - COMPLEXITY, 4 (4). No-045003. ISSN 2632-072X

Preview

Text Xiao_2023_J._Phys._Complex._4_045003.pdf - Published Version Available under License Creative Commons Attribution. Download (830kB) | Preview

Abstract

A social dilemma implies that individuals will choose the defection strategy to maximize their individual gains. Reward is a powerful motivator to promote the evolution of cooperation, thus addressing the social dilemma. Nevertheless, it is costly since we need to monitor all participants in the game. Inspired by these observations, we here propose an inexpensive protocol, a so-called sampling reward mechanism, and apply it to social dilemmas, including public goods game and collective-risk social dilemma. More precisely, the actual usage of reward depends on the portion of cooperators in the sample. We show that the average cooperation level can be effectively improved under high reward threshold and high reward intensity, albeit at the expense of reward cost. It is intriguing to discover that for the latter aspect, there is a critical threshold at which further increases in reward intensity have no significant effect on improving the cooperation level. Moreover, we find that the small sample size favors the evolution of cooperation while an intermediate sample size always results in a lower reward cost. We also demonstrate that our findings are robust and remain valid for both types of social dilemma.

Actions (login required)

Edit Item