English

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

Artificial Intelligence 2026-05-13 v1

Abstract

We propose a personal-LLM exchange (LLM-X), a scalable negotiation-oriented environment that enables direct, structured communication across populations of personal agents (LLMs), each representing an individual user. Unlike existing tool-centric protocols that focus on agent-API interaction, LLM-X introduces a message bus and routing substrate for LLM-to-LLM coordination with guarantees around schema validity and policy enforcement. We contribute: (1) an architecture for LLM-X comprising federated gateways, topic-based routing, and policy enforcement; (2) a typed message protocol supporting capability negotiation and contract-net-style coordination; and (3) the first empirical evaluation of LLM-based multi-agent negotiation at scale. Experiments span 5, 9, and 12 agents, under distinct negotiation policies (Low, Medium, High), and across both short-run (minutes) and long-run (2h, 12h) load conditions. Results highlight clear policy-performance trade-offs: stricter policies improve robustness and fairness but increase latencies and message volume. Extended runs confirm that LLM-X remains stable under sustained load, with bounded latency drift.

Keywords

Cite

@article{arxiv.2605.11376,
  title  = {LLM-X: A Scalable Negotiation-Oriented Exchange for Communication Among Personal LLM Agents},
  author = {Giuliano Lorenzoni and Paulo Alencar and Donald Cowan},
  journal= {arXiv preprint arXiv:2605.11376},
  year   = {2026}
}

Comments

8 pages, 7 figures, accepted at AGENT 2026 Workshop, co-located with ICSE 2026