Anonymous monitoring enables turn-taking and sustainablity in collective resource governance: Multi-player evolutionary dynamical-systems game

TL;DR

This paper models how anonymous monitoring can sustain collective resource management through self-organized turn-taking, showing that simple institutional rules emerge and adapt as populations grow, promoting efficiency and equity.

Contribution

It introduces a dynamical-systems game model demonstrating how anonymized information leads to self-organized turn-taking and institutional stability in large-scale resource governance.

Findings

Players form clusters that alternate harvesting turns.

Moderate diversity in strategies enhances cooperation and fairness.

Institutional stability depends on gradual population growth and adaptation.

Abstract

Sustainable resource use in large societies requires social institutions that specify acceptable behavior and punish violators. Because mutual monitoring becomes prohibitively costly as populations grow, we examine whether sustainability can be maintained when only anonymized information is available. Using the evolutionary dynamical-systems game framework, we model the common-pool resource management game. In the model, each player's harvesting decisions shape the resource dynamics and depend on the resource's state, the player's wealth, and the group average wealth. Strategies are encoded as two-parameter decision-making functions that mutate across generations. Evolutionary simulations reveal that players self-organize into clusters that alternate harvesting turns: individuals within a cluster harvest synchronously, while the clusters themselves take turns. The emergent institutional rule is strikingly simple: "wait when rich, harvest when below average." While the majority cluster tends to exploit the minority, moderate diversity in decision parameters of strategies allows "turn-taking of turns" between the majority and minority roles, improving efficiency, equity, and resistance to selfish mutants. We quantify the difficulty of managing institutions as population size increases. When group size is fixed, the minimum number of groups required for cooperation grows exponentially with group size. If, however, groups enlarge gradually, the scaling transitions to a power law, indicating that institutions remain stable when they are first built in small populations and subsequently adapted to larger ones. Our findings provide a theoretical basis for the self-organization of institutions in large societies, illuminating how anonymized information can coordinate behavior and how institutional success depends on its developmental trajectory.