AI Models & Assistants / Knowledge library
Multi-Agent Systems
Systems in which multiple autonomous agents coordinate or interact
Why learn Multi-Agent Systems?
Multiple agents can parallelize or critique work, but more agents do not guarantee a better answer.
Where it came from
Multi-agent designs assign roles, messages, shared state, or negotiation among multiple agents. They add coordination costs and failure modes as well as specialization.
Build your understanding
Work through these exercises in order. Try the task before opening a reference.
- Identify a multi-agent design: Which system is genuinely multi-agent?
- Assign clear roles: Why define explicit responsibilities for planner and executor agents?
- Prevent coordination loops: Two agents repeatedly delegate the same task to each other. What control helps?
- Protect delegated actions: Agent A asks Agent B to delete data. What must B verify?
- Justify added complexity: What comparison should precede adopting a multi-agent workflow?
Documentation and sources
- Primary reference (arxiv.org)