Stochastic swarm exploration models mimicking ant colony pheromone deposition to locate targets and optimize transport networks without central dispatchers.
Robots maintain a shared decentralized 2D spatial grid representing digital pheromone concentrations. Agents deposit virtual pheromones along successfully traversed paths, while mathematical evaporation algorithms prevent stagnation.
By steering toward negative pheromone gradients, the swarm maximizes spatial exploration speed during search-and-rescue sweeps, naturally covering large disaster zones with zero duplicate searches.