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Sagan

Paper

LLM-X: A Scalable Negotiation-Oriented Exchange for Communication Among Personal LLM Agents

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AI summary

The authors propose LLM-X, a message-bus architecture for direct communication and negotiation among personal LLM agents (each representing a user), rather than agents just calling APIs. It introduces federated gateways, topic-based routing, and policy enforcement to enable LLM-to-LLM coordination with schema validation and negotiation-style protocols (like contract-net). They run the first empirical evaluation of multi-agent LLM negotiation at scale (5–12 agents, low/medium/high negotiation policies, up to 12-hour runs), finding clear policy-performance tradeoffs: stricter policies improve robustness and fairness but increase latency and message volume. The system remains stable under sustained load.

Main takeaways:

  • LLM-X is a message-bus substrate for direct LLM-to-LLM communication and negotiation, not just agent-API tool use.
  • It combines federated gateways, topic-based routing, and typed message protocols with policy enforcement and capability negotiation.
  • First empirical evaluation of LLM-based multi-agent negotiation at scale: 5–12 agents, three policy strictness levels, runs up to 12 hours.
  • Stricter negotiation policies improve robustness and fairness but increase latency and message volume.
  • The system shows bounded latency drift under sustained multi-hour load, confirming stability.