Imitating opponent to win: Adversarial policy imitation learning in two-player competitive games

• Main Authors: BUI, The Viet, MAI, Tien, NGUYEN, Thanh H.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: Reinforcement Learning; Non-zero-sum Multi-agent Competition; Adversarial Policy; Imitation Learning; Artificial Intelligence and Robotics; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/8332; https://ink.library.smu.edu.sg/context/sis_research/article/9335/viewcontent/AAMAS23.pdf
• Institution: Singapore Management University

Recent research on vulnerabilities of deep reinforcement learning (RL) has shown that adversarial policies adopted by an adversary agent can influence a target RL agent (victim agent) to perform poorly in a multi-agent environment. In existing studies, adversarial policies are directly trained based...