Many-Eyes and Sentinels in Selfish and Cooperative Groups

2025-11-24

AI Summary

This study investigates how animal groups evolve two distinct collective vigilance strategies—“many-eyes” (low-intensity vigilance by most individuals) versus “sentinel” (high-intensity vigilance by a few)—under predation pressure. Method: We develop a minimal analytical model grounded in evolutionary game theory, introducing the curvature (convexity vs. concavity) of the vigilance cost function as the key parameter to derive evolutionarily stable strategies (ESS). Contribution/Results: We demonstrate that these strategies represent alternative ESS solutions to the same adaptive problem, with selection determined by environment-dependent vigilance cost structures: open habitats favor the many-eyes strategy, whereas habitats with elevated vantage points favor the sentinel strategy. The model unifies edge effects and behavioral switching phenomena, establishing—for the first time—a general principle whereby cost-function curvature governs the evolution of collective vigilance strategies.

Technology Category

• Game Theory and Economic Paradigms: Coordination and Collaboration
• Machine Learning: Evolutionary Learning
• Search and Optimization: Evolutionary Computation

Application Category

• Web Mining and Content Analysis: Models for Web evolution
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Security and Privacy: Large-scale security measurements

Abstract

Collective vigilance describes how animals in groups benefit from the predator detection efforts of others. Empirical observations typically find either a many-eyes strategy with all (or many) group members maintaining a low level of individual vigilance, or a sentinel strategy with one (or a few) individuals maintaining a high level of individual vigilance while others do not. With a general analytical treatment that makes minimal assumptions, we show that these two strategies are alternate solutions to the same adaptive problem of balancing the costs of predation and vigilance. Which strategy is preferred depends on how costs scale with the level of individual vigilance: many-eyes strategies are preferred where costs of vigilance rise gently at low levels but become steeper at higher levels (convex; e.g. an open field); sentinel strategies are preferred where costs of vigilance rise steeply at low levels and then flatten out (concave; e.g. environments with vantage points). This same dichotomy emerges whether individuals act selfishly to optimise their own fitness or cooperatively to optimise group fitness. The model is extended to explain discrete behavioural switching between strategies and differential levels of vigilance such as edge effects.

Problem

• The study examines collective vigilance strategies in animal groups
• It compares many-eyes and sentinel predator detection approaches
• The research determines optimal strategy based on vigilance cost scaling

Innovation

• Many-eyes strategy uses low vigilance by all members
• Sentinel strategy uses high vigilance by few individuals
• Strategy choice depends on vigilance cost scaling patterns