Stealthy and efficient adversarial attacks against deep reinforcement learning
Adversarial attacks against conventional Deep Learning (DL) systems and algorithms have been widely studied, and various defenses were proposed. However, the possibility and feasibility of such attacks against Deep Reinforcement Learning (DRL) are less explored. As DRL has achieved great success in...
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格式: | text |
語言: | English |
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Institutional Knowledge at Singapore Management University
2020
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在線閱讀: | https://ink.library.smu.edu.sg/sis_research/7116 https://ink.library.smu.edu.sg/context/sis_research/article/8119/viewcontent/6047_Article_Text_9272_1_10_20200513.pdf |
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