AI RESEARCH
Can AI Agents Agree?
arXiv CS.LG
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ArXi:2603.01213v2 Announce Type: replace-cross Large language models are increasingly deployed as cooperating agents, yet their behavior in adversarial consensus settings has not been systematically studied. We evaluate LLM-based agents on a Byzantine consensus game over scalar values using a synchronous all-to-all simulation. We test consensus in a no-stake setting where agents have no preferences over the final value, so evaluation focuses on agreement rather than value optimality.