Curiosity-driven and victim-aware adversarial policies

• Main Authors: GONG, Chen, YANG, Zhou, BAI, Yunpeng, SHI, Jieke, SINHA, Arunesh, XU, Bowen, LO, David, HOU, Xinwen, FAN, Guoliang
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Adversarial Attack; Reinforcement Learning; Curiosity Mechanism; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/7682; https://ink.library.smu.edu.sg/context/sis_research/article/8685/viewcontent/curiosity__1_.pdf
• Institution: Singapore Management University

Recent years have witnessed great potential in applying Deep Reinforcement Learning (DRL) in various challenging applications, such as autonomous driving, nuclear fusion control, complex game playing, etc. However, recently researchers have revealed that deep reinforcement learning models are vulner...