ASQ-IT: Interactive explanations for reinforcement-learning agents

Author:

Amitai YotamORCID,Amir OfraORCID,Avni GuyORCID

Funder

Israel Science Foundation

European Research Council

Publisher

Elsevier BV

Reference78 articles.

1. Trends and trajectories for explainable, accountable and intelligible systems: an hci research agenda;Abdul,2018

2. Formal methods with a touch of magic;Alamdari,2020

3. Highlights: summarizing agent behavior to people;Amir,2018

4. Y. Amitai, O. Amir, A survey of global explanations in reinforcement learning, in: Explainable Agency in Artificial Intelligence, CRC Press, pp. 21–42.

5. Y. Amitai, O. Amir, “I don't think so”: Summarizing policy disagreements for agent comparison, 2022.

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