ReCCoVER: Detecting Causal Confusion for Explainable Reinforcement Learning-Reference-Cited by-同舟云学术

ReCCoVER: Detecting Causal Confusion for Explainable Reinforcement Learning

Published:2022 Issue: Volume: Page:38-56
ISSN:0302-9743
Container-title:Explainable and Transparent AI and Multi-Agent Systems
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Author:

Gajcin Jasmina^ORCID,Dusparic Ivana^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-15565-9_3

Reference24 articles.

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3. Burkart, N., Huber, M.F.: A survey on the explainability of supervised machine learning. J. Artif. Intell. Res. 70, 245–317 (2021)

4. Carvalho, D.V., Pereira, E.M., Cardoso, J.S.: Machine learning interpretability: a survey on methods and metrics. Electronics 8(8), 832 (2019)

5. Chevalier-Boisvert, M., Willems, L., Pal, S.: Minimalistic gridworld environment for OpenAI Gym (2018). https://github.com/maximecb/gym-minigrid

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