Amir Samadi

SAFE-RL: Saliency-Aware Counterfactual Explainer for Deep Reinforcement Learning Policies

While Deep Reinforcement Learning (DRL) has emerged as a promising solution for intricate control tasks, the lack of explainability of the learned policies impedes its uptake in safety-critical applications, such as automated driving systems (ADS). Counterfactual (CF) explanations have recently gain