12.4. Boids¶
In 1987 Craig Reynolds published “Flocks, herds and schools: A distributed behavioral model”, which describes an agent-based model of herd behavior.
Agents in this model are called “Boids”, which is both a contraction of “bird-oid” and an accented pronunciation of “bird” (although Boids are also used to model fish and herding land animals).
Each agent simulates three behaviors:
Flock centering: Move toward the center of the flock.
Collision avoidance: Avoid obstacles, including other Boids.
Velocity matching: Align velocity (speed and direction) with neighboring Boids.
Boids make decisions based on local information only; each Boid only sees (or pays attention to) other Boids in its field of vision.
In the repository for this book, you will find Boids7.py, which contains an implementation of Boids, based in part on the description in Gary William Flake’s book, The Computational Beauty of Nature.
The given implementation uses VPython, which is a library that provides 3-D graphics. VPython provides a vector object, which can be used to represent the position and velocity of Boids in three dimensions.
- True
- Sorry but Boids only make decisions based on local information because they only pay attention to local Boids.
- False
- Correct!
Q-1: Boids make decisions based off of local information most of the time but they occasionally make decisions by looking at non local information.
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