Detecting the Collapse of Cooperation in Evolving Networks

TL;DR

This paper investigates how to detect early warning signs of cooperation collapse in evolving networks by combining dynamical network analysis and evolutionary game theory, focusing on the risk posed by cheaters.

Contribution

It introduces a method to estimate the collapse risk of cooperation in communities by analyzing structural and compositional changes caused by cheaters.

Findings

Risk of cooperation collapse increases as cheaters become harder to eliminate.

Community structure changes can serve as early warning signals.

Detection reliability depends on cheater evolution mechanisms.

Abstract

The sustainability of structured biological, social, economic and ecological communities are often determined by the outcome of social conflicts between cooperative and selfish individuals (cheaters). Cheaters avoid the cost of contributing to the community and can occasionally spread in the population leading to the complete collapse of cooperation. Although such a collapse often unfolds unexpectedly bearing the traits of a critical transition, it is unclear whether one can detect the rising risk of cheater's invasions and loss of cooperation in an evolving community. Here, we combine dynamical networks and evolutionary game theory to study the abrupt loss of cooperation as a critical transition. We estimate the risk of collapse of cooperation after the introduction of a single cheater under gradually changing conditions. We observe a systematic increase in the average time it takes for cheaters to be eliminated from the community as the risk of collapse increases. We detect this risk based on changes in community structure and composition. Nonetheless, reliable detection depends on the mechanism that governs how cheaters evolve in the community. Our results suggest possible avenues for detecting the loss of cooperation in evolving communities