Emergent stigmergy and pheromone-guided decisions in a foraging collective
Ants in a colony forage and recruit other nest-mates for cooperative transport of food through stigmergy. Traditional approach to capture the foraging dynamics relies on fine-tuning phenomenological rules for pheromone deposition, chemotaxis, evaporation, and behavioral switching after reaching the food source. Here, we show that stigmergy emerges from an infinite-horizon stochastic optimal control problem involving outbound foragers traveling from the nest to the food source and returning agents traveling from the food source to the nest. Pheromone dynamics along a trail emerge from the forward propagating Hamilton--Jacobi--Bellman (HJB) equation, with the Bellman discount rate setting the rate of pheromone evaporation. Using this mapping, we identify the conditions under which trail feedback suppresses exploration or leads to the exploitation of established trails. For ants exploring multiple trails, we also find flux-potential relations, analogous to Ohm's law, with ant flux and inverse of squared value field playing the roles of current and resistance on the network. Our model captures collective behavior observed in the classic double-bridge experiments: trail selection on identical routes through a symmetry-breaking instability, selection of the shorter bridge, and bistability in the trail-length ratio that can leave ants transiently committed to the longer route. Our formulation places collective foraging in the broader framework of stochastic optimal control, while simultaneously providing an unifying picture on their emergent behavior consistent with experimental observations.