Scalable multi-agent reinforcement learning for aggregation systems

• Main Author: VERMA, Tanvi
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Mult-Agent Reinforcement Learning; Aggregation Systems; Non-atomic Congestion Games; Large Agent Population; Non-cooperative Learning; Incentive Based Learning; Artificial Intelligence and Robotics; Systems Architecture
• Online Access: https://ink.library.smu.edu.sg/etd_coll/279; https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1279&context=etd_coll
• Institution: Singapore Management University

Efficient sequential matching of supply and demand is a problem of interest in many online to offline services. For instance, Uber, Lyft, Grab for matching taxis to customers; Ubereats, Deliveroo, FoodPanda etc. for matching restaurants to customers. In these systems, a centralized entity (e.g., Ube...