Hao Xiang Li — accepted AI-conference papers

2026

Scaling Multi-Agent Environment Co-Design with Diffusion Models

Hao Xiang Li, Michael Amir, Amanda Prorok

ICML 2026poster

The agent-environment co-design paradigm jointly optimises agent policies and environment configurations in search of improved system performance, promising to fundamentally reshape how we deploy multi-agent systems in domains such as warehouse logistics and windfarm management. However, current co-…

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2023

Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning

Joseph Suarez, David Bloomin, Kyoung Whan Choe, Hao Xiang Li, Ryan Sullivan, Nishaanth Kanna Ravichandran +10

NeurIPS 2023poster

Neural MMO 2.0 is a massively multi-agent and multi-task environment for reinforcement learning research. This version features a novel task-system that broadens the range of training settings and poses a new challenge in generalization: evaluation on and against tasks, maps, and opponents never see…

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