Boids Model
A computational model of flocking behavior developed by Craig Reynolds in 1986.
A computational model of flocking behavior developed by Craig Reynolds in 1986. The model demonstrates how complex, coordinated group behavior emerges from three simple rules followed by each individual agent (called a 'boid'): Separation (maintain minimum distance from neighbors), Alignment (match average velocity of nearby agents), and Cohesion (move toward average position of nearby agents). These local rules require no global coordination yet produce realistic flocking, schooling, and swarming behaviors.
When to Use Boids Model
Use the Boids model principles when designing decentralized coordination systems, understanding how simple local rules can generate complex global behaviors, or analyzing existing self-organizing systems to identify the underlying behavioral rules.
How to Apply
Separation
Each agent maintains a minimum distance from its neighbors to avoid collision and crowding. If neighbors are too close, the agent steers away.
Outputs
- Collision avoidance
- Distributed spacing
Alignment
Each agent matches the average velocity (speed and direction) of nearby agents, creating coordinated movement.
Outputs
- Coordinated direction
- Synchronized speed
Cohesion
Each agent moves toward the average position of nearby agents, keeping the group together.
Outputs
- Group cohesion
- Formation maintenance