Story · arXiv
When LLM Agents Negotiate: Private Information and Dynamic Bargaining in Supply Chains (arXiv)
paper · Story page
Nine LLMs negotiated 9,840 buyer-seller contracts against a game-theoretic benchmark. Agents captured 95.4% of first-best surplus, but slow bargaining eroded 21–34% of it, and baseline models accepted individually irrational contracts in 19.2% of cases.
In plain words
- Researchers ran 9,840 buyer-seller contract talks between nine artificial intelligence systems.
- Buyers privately knew expected demand, while sellers had to bargain without that information.
- Agreements were reached in 98.9% of talks, capturing 95.4% of the greatest possible combined gain before delays.
- However, longer talks reduced that gain by 21% to 34%, and basic systems accepted money-losing deals in 19.2% of cases.
- Companies using automated buyers may need profit checks, especially when their systems are not among the strongest tested.
Appeared in
- In LangChain's benchmark, only 7% of agent turns needed a frontier model
Aug 12, 2026 · in the sections
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