Constrained multiagent reinforcement learning for large agent population

• المؤلفون الرئيسيون: LING, Jiajing, SINGH, Arambam James, NGUYEN, Duc Thien, KUMAR, Akshat
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2022
• الموضوعات: Multi-agent systems; Multiagent reinforcement learning; Constraint optimization; Artificial Intelligence and Robotics; Databases and Information Systems
• الوصول للمادة أونلاين: 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
• المؤسسة: 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...