Amin Nikanjam, Mohammad Mehdi Morovati, Foutse Khomh and Houssem Ben Braiek
Article (2022)
An external link is available for this item| Department: | Department of Computer Engineering and Software Engineering |
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| PolyPublie URL: | https://publications.polymtl.ca/50474/ |
| Journal Title: | Automated Software Engineering (vol. 29, no. 1) |
| Publisher: | Springer |
| DOI: | 10.1007/s10515-021-00313-x |
| Official URL: | https://doi.org/10.1007/s10515-021-00313-x |
| Date Deposited: | 18 Apr 2023 14:59 |
| Last Modified: | 08 Apr 2025 07:18 |
| Cite in APA 7: | Nikanjam, A., Morovati, M. M., Khomh, F., & Ben Braiek, H. (2022). Faults in deep reinforcement learning programs: a taxonomy and a detection approach. Automated Software Engineering, 29(1), 8 (32 pages). https://doi.org/10.1007/s10515-021-00313-x |
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