VI · Multi-AgentExperimental·

Cellular-Automata Agents

also known as Local-Rule Swarm, Cellular Automaton Pattern

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.

This pattern helps complete certain larger patterns —

  • specialisesSwarm·— Run many peer agents that interact directly without a central supervisor, achieving emergent coordination.

Context

A team has a problem space (large grid, large graph, large population of entities) where state evolves over many steps. Centralized orchestration does not scale; agents with global state become a bottleneck. The problem has spatial or relational locality.

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.

Forces

  • Strict local-only information access constrains what agents can compute.
  • Emergent macro behavior is hard to predict from rules alone — must be tested in simulation.
  • Designing the local rule set is the engineering work; tuning it is iterative.

Example

A large-document analysis problem: each agent corresponds to a paragraph, neighborhood is the surrounding ±3 paragraphs. Local rule: 'if neighborhood mentions topic X and my paragraph doesn't, mark me as candidate-to-extend'. Over 10 iterations, coherent topic clusters emerge from local-only rules without any central topic planner.

Diagram

Solution

Therefore:

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.

What this pattern forbids. Each agent may read only its declared neighborhood; global queries and arbitrary peer access are forbidden.

And the patterns that stand alongside it, or against it —

  • alternative-toDecentralized Agent Network·— Agents publish signed DID+JSON-LD identity records so any peer can discover and verify them without a central registry — the agent equivalent of the open web.
  • alternative-toBlackboard·— Give multiple agents a shared, queryable workspace they can read from and write to as they collaborate.
  • complementsDecentralized Swarm Handoff★— Agents in a swarm decide handoffs to peers based on a shared protocol with no central coordinator; specifically about agent-initiated handoff protocols, not topology.
  • complementsActor-Model Agents★— Implement each agent as an independent actor with its own mailbox, processing asynchronous messages one at a time and never sharing mutable state with peers.

Neighbourhood

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References

Provenance