Home▸AI & Machine Learning▸Modelling a Beehive: Agent-Based Simulation Engine

🧮 Modelling a Beehive: Agent-Based Simulation Engine

A 3D look inside the computational engine behind beehive simulations: thousands of instanced bee-agents, a spatial hash grid for fast neighbour queries, a diffusing pheromone field, and patriline genetics you can toggle live.

AI & Machine Learning3DAdvanced60 FPS

A 3D view of the computational machinery behind beehive agent-based models: thousands of instanced bee-agents shuttling between hive and flower patch, a spatial hash grid speeding up neighbour queries, and a diffusing pheromone field standing in for chemical communication.

🔬 What It Demonstrates

Spatial hashing turns an O(n²) neighbour search into a cheap local lookup; a coarse pheromone field shows how diffusion and evaporation are approximated frame-by-frame; and patriline colouring reveals the genetic structure researchers track alongside behaviour.

🎮 How to Use

Raise the agent count to see how the grid and frame rate respond, adjust the neighbour radius to resize the spatial-hash cells and the focus bee's search sphere, tune pheromone evaporation, and switch colouring between task-role and genetic patriline.

💡 Did You Know?

Large-scale honeybee ABMs such as BEEHAVE simulate tens of thousands of bees and brood cells across a full season — feasible only because of exactly these tricks: spatial partitioning, cheap per-agent rules, and simplified diffusion fields.

⚙ Under the hood

agent-based simulationartificial intelligencebeesmodelingsimulationThree.js

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