Transition-informed reinforcement learning for large-scale Stackelberg mean-field games.

• Main Authors: LI, Pengdeng, YU, Runsheng, WANG, Xinrun, AN, Bo
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Multiagent Learning; Reinforcement Learning; Artificial Intelligence and Robotics; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/9127; https://ink.library.smu.edu.sg/context/sis_research/article/10130/viewcontent/29696_Transition_InformedRL_pvoa.pdf
• Institution: Singapore Management University

Many real-world scenarios including fleet management and Ad auctions can be modeled as Stackelberg mean-field games (SMFGs) where a leader aims to incentivize a large number of homogeneous self-interested followers to maximize her utility. Existing works focus on cases with a small number of heterog...