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Evidence record 5285 · automatically gathered

Cooperate to Compete: Strategic Coordination in Multi-Agent Conquest

Language Model (LM)-based agents remain largely untested in mixed-motive settings where agents must leverage short-term cooperation for long-term competitive goals (e.g., multi-party politics). We introduce Cooperate to Compete (C2C), a multi-agent environment where players can engage in private negotiations while competing to be the first to achieve their secret objective. Players have asymmetric objectives and negotiations are non-binding, allowing alliances to form and break as players' short

Record details

Published: 28 April 2026
Source: arXiv
Category: Research
Topics: Agents & autonomy · Environment
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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How to cite this record

ethics.ai (28 April 2026), “Cooperate to Compete: Strategic Coordination in Multi-Agent Conquest,” evidence record 5285, https://ethics.ai/record/5285 (originally published by arXiv).

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