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Jamal Bentahar

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#machine learning Preprint Sep 2026

Robust Policy Optimization via Adversarial Importance Sampling

This work introduces Adversarial Importance Sampling (Advis), a method that uses importance sampling over trajectories from standard training to estimate and optimize verifiable worst-case returns and introduces advrl, a modular PyTorch library that provides clean, single-file implementations of existing robustness met...

Amine Andam, Jamal Bentahar, M. Hedabou · 0 citations