Zain Ulabedeen Farhat — accepted AI-conference papers

2026

Sample-Efficient Distributionally Robust Multi-Agent Reinforcement Learning via Online Interaction

Zain Ulabedeen Farhat, Debamita Ghosh, George K. Atia, Yue Wang

ICLR 2026poster

Well-trained multi-agent systems can fail when deployed in real-world environments due to model mismatches between the training and deployment environments, caused by environment uncertainties including noise or adversarial attacks. Distributionally Robust Markov Games (DRMGs) enhance system resilie…

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2025

Model-Free Offline Reinforcement Learning with Enhanced Robustness

Chi Zhang, Zain Ulabedeen Farhat, George K. Atia, Yue Wang

ICLR 2025poster

Offline reinforcement learning (RL) has gained considerable attention for its ability to learn policies from pre-collected data without real-time interaction, which makes it particularly useful for high-risk applications. However, due to its reliance on offline datasets, existing works inevitably in…

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