Cellular-Automata Agents
A swarm where each agent applies simple local rules to its immediate neighborhood; macro behavior emerges without a central orchestrator and without global information access.
Problem
Centralized agent designs do not scale to large grids/populations because every step requires global information. Distributed designs that allow agents to query arbitrary peers introduce coordination overhead that dominates the computation. The pattern of 'simple local rules → complex emergent macro behavior' from cellular automata is not standardly applied to agent design.
Solution
Each agent has (state, neighborhood_radius=k, local_rule). At each step, agent reads only the k-radius neighborhood and applies the local rule to produce next state. No global state, no peer queries beyond the radius. Macro behavior is observed in simulation, not specified. Distinct from decentralized-agent-network (which allows arbitrary peer queries) and swarm (which is broader). Pair with decentralized-agent-network, swarm.
When to use
- Large grid/graph problems with spatial or relational locality.
- Per-agent cost must be bounded independent of population size.
- Emergent macro behavior is acceptable as outcome metric.
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