Evolution of cooperation driven by sampling punishment

Xiao, Jiafeng; Liu, Linjie; Chen, Xiaojie; Szolnoki, Attila

doi:10.1016/j.physleta.2023.128879

Cited by 13 publications

(3 citation statements)

References 66 publications

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“…Nevertheless, the pursuit of cooperation and punishment system design is not confined solely to mathematical models and logical reasoning but also hinges deeply on the philosophical and neurological realms of ethics, power, justice, and sovereignty 74 . Indeed, punishment in the PGG is generally a highly interdisciplinary subject, with significant contributions coming from economics 17 , 29 , 38 , social sciences 4 , 56 , 75 , network science 24 , 76 , 77 , physics 22 , 36 , 42 , 64 , and even moral and ethical studies 71 . Hence, it encompasses a lively interplay between the physical manifestations of actions, the logical aspects that shape their foundation, the moral assessments that assign their worth, and the political structures that sustain and control them 71 , 78 .…”

Section: Discussionmentioning

confidence: 99%

“…Wang et al 61 – 63 have recently explored strategies to minimize the costs associated with sanctioning by optimizing incentives where decentralized systems are in place. Similarly, Xiao et al 64 have proposed a cost-reduction approach by monitoring a subset of the group rather than the entire population, presenting an efficient method for implementing oversight and sanctioning mechanisms. Although current research has shed light on the effectiveness of centralized incentive systems in promoting cooperation within social dilemmas, several key questions are still open.…”

Section: Introductionmentioning

confidence: 99%

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Discipline and punishment in panoptical public goods games

Botta,

Blanco,

Schaerer

2024

Sci Rep

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In Public Goods Games (PGG), the temptation to free-ride on others’ contributions poses a significant threat to the sustainability of cooperative societies. Therefore, societies strive to mitigate this through incentive systems, employing rewards and punishments to foster cooperative behavior. Thus, peer punishment, in which cooperators sanction defectors, as well as pool punishment, where a centralized punishment institution executes the punishment, is deeply analyzed in previous works. Although the literature indicates that these methods may enhance cooperation on social dilemmas under particular contexts, there are still open questions, for instance, the structural connection between graduated punishment and the monitoring of public goods games. Our investigation proposes a compulsory PGG framework under Panoptical surveillance. Inspired by Foucault’s theories on disciplinary mechanisms and biopower, we present a novel mathematical model that scrutinizes the balance between the severity and scope of punishment to catalyze cooperative behavior. By integrating perspectives from evolutionary game theory and Foucault’s theories of power and discipline, this research uncovers the theoretical foundations of mathematical frameworks involved in punishment and discipline structures. We show that well-calibrated punishment and discipline schemes, leveraging the panoptical effect for universal oversight, can effectively mitigate the free-rider dilemma, fostering enhanced cooperation. This interdisciplinary approach not only elucidates the dynamics of cooperation in societal constructs but also underscores the importance of integrating diverse methodologies to address the complexities of fostering cooperative evolution.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Discipline and punishment in panoptical public goods games

Botta,

Blanco,

Schaerer

2024

Sci Rep

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show abstract

“…In particular, Xiao et al investigated the sampling punishment mechanism, which involves different scales of sanctioning for the population. They found it can help improve the cooperation level under low punishment threshold and small sample size when punishment intensity is considerable [44].…”

Section: Introductionmentioning

confidence: 99%

Evolution of cooperation driven by sampling reward

Xiao,

Liu,

Chen

et al. 2023

J. Phys. Complex.

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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 dilemmas.

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