HomeAlgorithms & AIAnt Colony Double-Bridge Experiment

Ant Colony Double-Bridge Experiment

A 3D reconstruction of Deneubourg's classic asymmetric double-bridge experiment: watch a live ant colony choose between a short and a long path, laying and evaporating pheromone, and converge on the shorter route through pure positive feedback.

Algorithms & AI3DModerate60 FPS📱 Mobile-adapted⇄ 2D version
ant-colony-pheromone-trail-optimization ↗ Open standalone

A colony of ants connects its nest to a food source over two bridges of different length, and this simulator reconstructs the exact mechanism biologists used to explain how they end up almost always on the shorter one. No ant measures distance or compares the branches — each simply deposits evaporating pheromone on whichever branch it just walked and, at the next fork, chooses probabilistically in favor of whichever branch already smells stronger. Because trips on the short branch finish faster, that branch accumulates reinforcement faster too, and the imbalance snowballs through nothing but positive feedback. Adjust the length ratio, evaporation rate and the nonlinearity of the choice rule to see when the colony converges cleanly on the shorter path, when it stays split, and when it can even lock onto the longer one by chance — the same dynamics that inspired Ant Colony Optimization as a search algorithm.

⚙ Under the hood

A 3D reconstruction of Deneubourg's classic asymmetric double-bridge experiment: watch a live ant colony choose between a short and a long path, laying and evaporating pheromone, and converge on the shorter route through pure positive feedback.

ant colony optimizationpheromone trailstigmergyswarm intelligencepositive feedbackmetaheuristic

3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install

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