Author

George Atia

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#artificial intelligence Preprint Sep 2026

Interactive Distributionally Robust Multi-Agent Learning with General Function Approximation

Model misspecification poses a fundamental challenge in multi-agent reinforcement learning, where transition uncertainty can be amplified by strategic interactions among agents. Distributionally robust Markov games (DRMGs) provide a principled framework for addressing such uncertainty, yet existing methods often rely o...

Debamita Ghosh, George Atia, Yue Wang · 0 citations

#machine learning Preprint Sep 2026

Vector Bellman Theory for Multichain Robust Average-Reward Markov Decision Processes

Robust average-reward Markov decision processes provide a fundamental framework for long-term performance optimization under uncertainty, and can have optimal long-run rewards that depend on the initial state. This state dependence requires a vector Bellman theory that accounts for both recurrent-class rewards and tran...

Yue Wang, George Atia · 0 citations