Adaptive Punishment in Social Dilemmas
Physics and Society
2025-12-11 v1
Abstract
We introduce a coevolutionary framework in which punishment intensity dynamically adapts to the fraction of cooperators in the population. Unlike static models, adaptive punishment reshapes the effective payoff landscape, driving transitions among canonical games, including the Prisoner's Dilemma, Harmony, Stag Hunt, and Chicken games. Analytical results reveal rich dynamical behaviors such as coexistence, bistability, limit cycle and Hopf bifurcation. These findings highlight adaptive punishment as a robust mechanism for sustaining cooperation by the coevolutionary feedback and offer insights into institutional design, ecological interactions, and social governance.
Keywords
Cite
@article{arxiv.2512.09450,
title = {Adaptive Punishment in Social Dilemmas},
author = {Xingfu Ke and Hao Yu and Xiao-Pu Han and Yi-Cheng Zhang and Fanyuan Meng},
journal= {arXiv preprint arXiv:2512.09450},
year = {2025}
}
Comments
5 pages, 5 figures