Vahid Behzadan, William Hsu. RL-Based Method for Benchmarking the Adversarial Resilience and Robustness of Deep Reinforcement Learning Policies. In Alexander B. Romanovsky, Elena Troubitsyna, Ilir Gashi, Erwin Schoitsch, Friedemann Bitsch, editors, Computer Safety, Reliability, and Security - SAFECOMP 2019 Workshops, ASSURE, DECSoS, SASSUR, STRIVE, and WAISE, Turku, Finland, September 10, 2019, Proceedings. Volume 11699 of Lecture Notes in Computer Science, pages 314-325, Springer, 2019. [doi]
@inproceedings{BehzadanH19-0,
title = {RL-Based Method for Benchmarking the Adversarial Resilience and Robustness of Deep Reinforcement Learning Policies},
author = {Vahid Behzadan and William Hsu},
year = {2019},
doi = {10.1007/978-3-030-26250-1_25},
url = {https://doi.org/10.1007/978-3-030-26250-1_25},
researchr = {https://researchr.org/publication/BehzadanH19-0},
cites = {0},
citedby = {0},
pages = {314-325},
booktitle = {Computer Safety, Reliability, and Security - SAFECOMP 2019 Workshops, ASSURE, DECSoS, SASSUR, STRIVE, and WAISE, Turku, Finland, September 10, 2019, Proceedings},
editor = {Alexander B. Romanovsky and Elena Troubitsyna and Ilir Gashi and Erwin Schoitsch and Friedemann Bitsch},
volume = {11699},
series = {Lecture Notes in Computer Science},
publisher = {Springer},
isbn = {978-3-030-26250-1},
}