Multi-agent colony
Micro-clusters of peers with filament hand-offs.
Verified against github.com
A swarm is a colony of peer agents that self-organise around a task, handing work to whichever peer is best placed rather than routing through a centre. Coordination is emergent: agents broadcast, claim and hand off sub-tasks, so the system scales horizontally and degrades gracefully when a peer drops out. The trade is control: with no single orchestrator, behaviour is harder to predict, bound and audit. In anatomy terms it is many reasoning cores sharing memory and transports, with no hub.
Many peer reasoning cores share memory and transports; coordination is emergent (broadcast, claim, hand-off) rather than centralised; the perimeter must gate each peer independently.
- ·Large-scale parallel research or data-gathering across many sources.
- ·Simulation and multi-role scenarios where peers play distinct parts.
- ·Resilience-critical workloads where no single node should be able to fail the job.
- ·Scales horizontally: add peers to add throughput.
- ·Graceful degradation: losing a peer does not stop the colony.
- ·Good for genuinely parallel, decomposable work.
- ·No orchestrator bottleneck.
- ·Emergent behaviour is hard to predict and bound.
- ·Auditing and safety-gating every peer is harder.
- ·Coordination chatter can dominate the useful work.
- ·Convergence is not guaranteed.
Mapping classified by the Field Book from each agent's documented control flow.
Description, use cases and trade-offs: Field Book analysis, synthesised from established agent-architecture literature.
The corpus does not rewrite vendor documentation. Where copy is quoted verbatim it is marked as such and attributed to its source.