3 papers
cs.LG2026
Online Robust Reinforcement Learning with General Function Approximation
Debamita Ghosh, George K. Atia, Yue Wang
In many real-world settings, reinforcement learning systems suffer performance degradation when the environment encountered at deployment differs from that observed during training…
cs.LG2026
Sample-Efficient Distributionally Robust Multi-Agent Reinforcement Learning via Online Interaction
Zain Ulabedeen Farhat, Debamita Ghosh, George K. Atia +1
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 u…
cs.LG2025
ORVIT: Near-Optimal Online Distributionally Robust Reinforcement Learning
Debamita Ghosh, George K. Atia, Yue Wang
We investigate reinforcement learning (RL) in the presence of distributional mismatch between training and deployment, where policies trained in simulators often underperform in pr…