Field · 6 models
Agent-Based Models and Cellular Automata
In an agent-based model, behavior is specified for individuals — cells, birds, households, wolves — and the pattern at the scale of the whole system is left to emerge. The same idea on a fixed grid of cells with identical rules is a cellular automaton.
Models in this field
- OS-022Game of LifeTwo rules on a grid of cells: gliders, guns, oscillators and soups that settle or keep going.
- OS-023Elementary cellular automataOne row of cells, eight neighborhood cases, 256 rules: from blank rows to chaos and universal computation.
- OS-024Schelling segregationAgents with mild preferences for similar neighbors sort themselves into strongly segregated clusters.
- OS-025Boids flockingSeparation, alignment and cohesion: three local steering rules that turn random headings into a flock.
- OS-026Forest fire modelTrees grow, lightning strikes, fires spread: a cellular automaton with fires of every size.
- OS-027Predator–preyWolves, sheep and grass on a grid: noisy population cycles, a phase loop and the risk of extinction.
Rules versus equations
Equation-based models such as the Lotka–Volterra equations describe averages: population densities that change smoothly. Agent-based models describe individuals, so they naturally include chance, spatial structure, local crowding and the extinction of small groups. The price is that results are random and must be summarized over runs, and parameters are harder to interpret. Comparing the agent-based predator–prey model with its equation counterpart makes the trade visible.
The models
- Conway’s Game of Life and elementary cellular automata: deterministic rules on a grid, from still lifes to Rule 110’s universal computation.
- Forest fire: growth and lightning on a grid, with fire sizes spanning orders of magnitude.
- Schelling segregation: households with mild preferences about their neighbors, and the strongly sorted pattern that can result.
- Boids: three steering rules per bird and flocks without a leader.
- Predator–prey: wolves, sheep and grass with energy budgets and reproduction.
Emergence is not explanation
A model that reproduces a pattern shows that its rules are sufficient to produce it, not that they are the cause in the real system. Schelling’s model shows that segregation can arise from mild preferences; it does not show that real segregation does. Each page states what its rules leave out.