The Co-evolution of Costly Signaling and Cooperation in Social Dilemmas

2026-05-13

AI Summary

This study investigates the coevolutionary dynamics of costly cooperation and costly signaling in the Prisoner’s Dilemma, Snowdrift, and Stag Hunt games. Employing a multi-agent model, individuals dynamically adjust their cooperative strategies based on observed signals, with evolutionary processes simulated across well-mixed populations, spatial lattices, and dynamic strategy environments. The results reveal that the evolutionary advantage of signaling stems primarily from its elicitation of cooperative responses rather than its production cost. Transient correlations prove crucial for sustaining cooperation in the Prisoner’s Dilemma, while spatial structure further enhances cooperation through local clustering. Combining mean-field analysis with cross-game comparisons, the theoretical framework successfully captures the evolutionary dynamics of the Snowdrift and Stag Hunt games; however, reproducing simulation outcomes for the Prisoner’s Dilemma requires explicit incorporation of transient correlations.

Abstract

Costly cooperation and costly signaling are both difficult to reconcile with simple fitness maximization, yet both are common in biological and social systems. We study a model in which agents emit costly signals and condition their actions on the signals they observe. Across the Prisoner's Dilemma (PD), Snowdrift (SD), and Stag Hunt (SH) games, we ask when this coevolutionary process can sustain cooperation and how it changes across well-mixed populations, spatial lattices, and fluctuating strategic environments. The simulations show that signals are selected less by their raw production costs than by the cooperative responses they currently elicit. In well-mixed populations, the mechanism sustains partial cooperation in PD and SD and drives near-complete cooperation in SH. On lattices, cooperation is strengthened further by local assortment. A reduced mean-field analysis explains why average population feedback is already sufficient in SD and SH, but not in the PD. To account for the PD dynamics, the reduced theory must include transient correlations associated with rare signals, inheritance, or spatial clustering. Our results therefore delineate a class of settings in which costly signals persist because they transiently organize cooperative responses and thereby reshape the effective strategic environment.

Problem

• costly signaling
• cooperation
• social dilemmas
• coevolution
• evolutionary dynamics

Innovation

• costly signaling
• coevolution
• social dilemmas
• spatial structure
• mean-field analysis