Swarm
Many peer agents interact through a shared bus or environment with no central supervisor — coordination is emergent, scale is horizontal, and termination is environment-level.
Intent & Description
🎯 Intent
Run many peer agents that interact directly without a central supervisor, achieving emergent coordination.
📋 Context
A task benefits from many independent attempts or interactions rather than a single coordinated plan — a negotiation simulation with many parties, a market simulation, an exploration of a large state space. Centralised coordination would either bottleneck the system or impose a single policy on agents that need to behave differently from each other.
💡 Solution
Agents interact via a shared message bus, chat, or environment. Each agent has its own goals and policies. No central coordinator; convergence is emergent. Termination conditions are environment-level (time budget, consensus threshold, external trigger).
Real-world Use Case
- Centralised coordination is a bottleneck or the task benefits from many independent simultaneous attempts.
- Agents can interact through a shared bus or environment.
- Termination conditions can be defined at the environment level.
Source
📌 TL;DR
Many peer agents, shared bus, no coordinator — emergent coordination from local interactions, horizontal scale, termination defined at the environment level.
Advantages
- Scales horizontally — add more agents without redesigning the coordination layer.
- Naturally suits negotiation simulation, market modeling, and large-scale exploration.
Disadvantages
- Hard to debug — emergent failures are global and lack a clear owner.
- Cost can balloon without supervision; individual agent spending needs governance.