MLSP-35.4
QRELATION: AN AGENT RELATION-BASED APPROACH FOR MULTI-AGENT REINFORCEMENT LEARNING VALUE FUNCTION FACTORIZATION
Siqi Shen, Jun Liu, Mengwei Qiu, Weiquan Liu, Cheng Wang, Xiamen University, China; Yongquan Fu, Qinglin Wang, Peng Qiao, National University of Defense Technology, China, China
Session:
Reinforcement Learning II
Track:
Machine Learning for Signal Processing
Location:
Gather Area H
Presentation Time:
Wed, 11 May, 21:00 - 21:45 China Time (UTC +8)
Wed, 11 May, 13:00 - 13:45 UTC
Wed, 11 May, 13:00 - 13:45 UTC
Session Co-Chairs:
Chang D Yoo, KAIST and Jochen Ehnes, Institute for Infocomm Research, A*STAR
Session MLSP-35
MLSP-35.1: DENOISING-ORIENTED DEEP HIERARCHICAL REINFORCEMENT LEARNING FOR NEXT-BASKET RECOMMENDATION
Qihan Du, Li Yu, Huiyuan Li, Youfang Leng, Ningrui Ou, Renmin University of China, China
MLSP-35.2: COMPETITIVE MULTI-AGENT REINFORCEMENT LEARNING WITH SELF-SUPERVISED REPRESENTATION
DiJia Su, Jason D. Lee, John M. Mulvey, H. Vincent Poor, Princeton University, United States of America
MLSP-35.3: MODEL-BASED ONLINE LEARNING FOR RESOURCE SHARING IN JOINT RADAR-COMMUNICATION SYSTEMS
Petteri Pulkkinen, Aalto University, Saab Finland Oy, Finland; Visa Koivunen, Aalto University, Finland
MLSP-35.4: QRELATION: AN AGENT RELATION-BASED APPROACH FOR MULTI-AGENT REINFORCEMENT LEARNING VALUE FUNCTION FACTORIZATION
Siqi Shen, Jun Liu, Mengwei Qiu, Weiquan Liu, Cheng Wang, Xiamen University, China; Yongquan Fu, Qinglin Wang, Peng Qiao, National University of Defense Technology, China, China
MLSP-35.5: DENOISING-GUIDED DEEP REINFORCEMENT LEARNING FOR SOCIAL RECOMMENDATION
Qihan Du, Li Yu, Huiyuan Li, Youfang Leng, Ningrui Ou, Junyao Xiang, Renmin University of China, China