Constrained multiagent reinforcement learning for large agent population

• Main Authors: LING, Jiajing, SINGH, Arambam James, NGUYEN, Duc Thien, KUMAR, Akshat
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Multi-agent systems; Multiagent reinforcement learning; Constraint optimization; Artificial Intelligence and Robotics; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/7672; https://ink.library.smu.edu.sg/context/sis_research/article/8675/viewcontent/Constrained_multiagent_reinforcement_learning_for_large_agent_population.pdf
• Institution: Singapore Management University

Learning control policies for a large number of agents in a decentralized setting is challenging due to partial observability, uncertainty in the environment, and scalability challenges. While several scalable multiagent RL (MARL) methods have been proposed, relatively few approaches exist for large...