Ant Colony Pheromone Trail Optimization

Ants forage from nest to food, laying pheromone trails. Shorter paths accumulate more pheromone and attract more ants — emergent path optimization.

Ants: 50 Food collected: 0 Best path: — Step: 0
Ant count: 50
Evaporation: 0.02
Deposit: 5.0
Randomness: 0.15

Stigmergic Optimization

Ants communicate indirectly through the environment (stigmergy). Each ant probabilistically follows pheromone gradients: P(direction) ∝ τ^α · η^β where τ is pheromone level and η is heuristic desirability. Shorter paths are traversed more frequently per unit time, accumulating more pheromone before it evaporates — positive feedback amplifies the shortest path. This mirrors ACO (Ant Colony Optimization) algorithms used for the Travelling Salesman Problem and network routing.