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cs.AI2023
Explaining Reinforcement Learning Agents Through Counterfactual Action Outcomes
Yotam Amitai, Yael Septon, Ofra Amir
Explainable reinforcement learning (XRL) methods aim to help elucidate agent policies and decision-making processes. The majority of XRL approaches focus on local explanations, see…
cs.AI2023
ASQ-IT: Interactive Explanations for Reinforcement-Learning Agents
Yotam Amitai, Guy Avni, Ofra Amir
As reinforcement learning methods increasingly amass accomplishments, the need for comprehending their solutions becomes more crucial. Most explainable reinforcement learning (XRL)…