Punishment in Public Goods games leads to meta-stable phase transitions and hysteresis

TL;DR

This paper investigates how punishment influences cooperation in public goods games, revealing that it can cause meta-stable phase transitions and hysteresis, thereby stabilizing cooperation or defection depending on conditions.

Contribution

It demonstrates that punishment induces meta-stable phase transitions and hysteresis in public goods games, providing a new understanding of cooperation stability.

Findings

Punishment lowers the critical synergy threshold for cooperation.

Punishment creates meta-stable states allowing cooperation below the critical point.

Hysteresis effects demonstrate the system's dependence on history and initial conditions.

Abstract

The evolution of cooperation has been a perennial problem in evolutionary biology because cooperation can be undermined by selfish cheaters who gain an advantage in the short run, while compromising the long-term viability of the population. Evolutionary game theory has shown that under certain conditions, cooperation nonetheless evolves stably, for example if players have the opportunity to punish cheaters that benefit from a public good yet refuse to pay into the common pool. However, punishment has remained enigmatic because it is costly, and difficult to maintain. On the other hand, cooperation emerges naturally in the Public Goods game if the synergy of the public good (the factor multiplying the public good investment) is sufficiently high. In terms of this synergy parameter, the transition from defection to cooperation can be viewed as a phase transition with the synergy as the critical parameter. We show here that punishment reduces the critical value at which cooperation occurs, but also creates the possibility of meta-stable phase transitions, where populations can "tunnel" into the cooperating phase below the critical value. At the same time, cooperating populations are unstable even above the critical value, because a group of defectors that are large enough can "nucleate" such a transition. We study the mean-field theoretical predictions via agent-based simulations of finite populations using an evolutionary approach where the decisions to cooperate or to punish are encoded genetically in terms of evolvable probabilities. We recover the theoretical predictions and demonstrate that the population shows hysteresis, as expected in systems that exhibit super-heating and super-cooling. We conclude that punishment can stabilize populations of cooperators below the critical point, but it is a two-edged sword: it can also stabilize defectors above the critical point.