How can LLMs collaborate globally for complex tasks?
DAWN: Designing Distributed Agents in a Worldwide Network
October 31, 2024
https://arxiv.org/pdf/2410.22339DAWN (Distributed Agents in a Worldwide Network) is a framework for building applications that use multiple AI agents, especially LLM-based ones, working together across the globe.
Key points for LLM-based multi-agent systems:
- Scalability: DAWN addresses the challenge of connecting many geographically distributed agents, unlike existing systems like LangGraph and AutoGen, which have limited scalability.
- Determinism and Flexibility: DAWN offers different operational modes (No-LLM, Copilot, LLM Agent) to balance the need for both flexible AI decision-making and predictable outcomes.
- Security: A dedicated security layer addresses vulnerabilities specific to LLM agents, such as prompt injection and knowledge poisoning, as well as general security concerns in a distributed system.
- Principal Agent and Gateway Agents: The Principal Agent acts as a central planner, creating plans and requesting resources. Gateway Agents, distributed globally, maintain registries of available resources (tools, LLMs, other agents) and respond to the Principal Agent's requests.
- Modular Architecture: DAWN's modular design allows flexibility and integration with diverse tools and agents. It also incorporates a communication layer, context layer (for memory and history), and orchestration layer (for workflow management).
- Real-world Application: The paper demonstrates DAWN's applicability with a human resources use case, showcasing its ability to handle both autonomous agent actions and human-in-the-loop processes.