Mimicking to dominate: Imitation learning strategies for success in multiagent competitive games

• Main Authors: BUI, The Viet, MAI, Tien, NGUYEN, Hong Thanh
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Multi-agent reinforcement learning; Imitation learning; Inverse Q learning; Artificial Intelligence and Robotics; Computer Sciences
• Online Access: https://ink.library.smu.edu.sg/sis_research/9788; https://ink.library.smu.edu.sg/context/sis_research/article/10788/viewcontent/NeurIPS2024___IL_for_Competitive_Multi_agent_Games__1_.pdf
• Institution: Singapore Management University

Training agents in multi-agent games presents significant challenges due to their intricate nature. These challenges are exacerbated by dynamics influenced not only by the environment but also by strategies of opponents. Existing methods often struggle with slow convergence and instability. To addre...