arXiv AI October 27, 2026 By Yi Loo, Akshunn Trivedi, Malika Meghjani

Efficient Generation of Diverse Cooperative Agents with World Models

The paper introduces XPM-WM, a framework that uses learned world models to generate simulated trajectories for Cross-play Minimization (XPM) in Zero-Shot Coordination. By replacing costly Mixed-Play sampling with model-generated data, XPM-WM improves sample efficiency and scales linearly with population size, producing diverse partner agents that match the performance of existing methods. The approach also bootstraps training for subsequent agents and can be extended to other population‑based training techniques.

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agents reinforcement-learning benchmarks safety

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PopGen: Generating Semantically Diverse Populations for Zero-Shot Coordination

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