3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Reward-Preserving Attacks For Robust Reinforcement Learning
Lucas Schott, Elies Gherbi, Hatem Hajri +1
Adversarial training in reinforcement learning (RL) is challenging because perturbations cascade through trajectories and compound over time, making fixed-strength attacks either o…
cs.LG2024★ 3 cited
Robust Deep Reinforcement Learning Through Adversarial Attacks and Training : A Survey
Lucas Schott, Josephine Delas, Hatem Hajri +5
Deep Reinforcement Learning (DRL) is a subfield of machine learning for training autonomous agents that take sequential actions across complex environments. Despite its significant…
cs.LG2020
Stochastic sparse adversarial attacks
Manon Césaire, Lucas Schott, Hatem Hajri +2
This paper introduces stochastic sparse adversarial attacks (SSAA), standing as simple, fast and purely noise-based targeted and untargeted attacks of neural network classifiers (N…