Sample-Based Rule Extraction for Explainable Reinforcement Learning-Reference-Cited by-同舟云学术

Sample-Based Rule Extraction for Explainable Reinforcement Learning

Published:2023 Issue: Volume: Page:330-345
ISSN:0302-9743
Container-title:Machine Learning, Optimization, and Data Science
language:
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Author:

Engelhardt Raphael C.^ORCID,Lange Moritz^ORCID,Wiskott Laurenz^ORCID,Konen Wolfgang^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-25599-1_25

Reference19 articles.

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2. Breiman, L., Friedman, J.H., Olshen, R.A., Stone, C.J.: Classification and Regression Trees. Routledge, London (1984)

3. Brockman, G., et al.: OpenAI Gym (2016). https://arxiv.org/abs/1606.01540

4. Coppens, Y., Efthymiadis, K., et al.: Distilling deep reinforcement learning policies in soft decision trees. In: Proceedings of IJCAI 2019 Workshop on Explainable Artificial Intelligence, pp. 1–6 (2019)

5. Fujimoto, S., van Hoof, H., Meger, D.: Addressing function approximation error in actor-critic methods. In: Dy, J., Krause, A. (eds.) Proceedings of 35th ICML, pp. 1587–1596. PMLR (2018)

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