MLSP-27: Reinforcement Learning 3 |
Session Type: Poster |
Time: Thursday, 10 June, 13:00 - 13:45 |
Location: Gather.Town |
Virtual Session: View on Virtual Platform |
Session Chair: Seung-Jun Kim, University of Maryland, Baltimore County |
MLSP-27.1: GAUSSIAN PROCESS TEMPORAL-DIFFERENCE LEARNING WITH SCALABILITY AND WORST-CASE PERFORMANCE GUARANTEES |
Qin Lu; University of Minnesota |
Georgios B. Giannakis; University of Minnesota |
MLSP-27.2: SELF-INFERENCE OF OTHERS' POLICIES FOR HOMOGENEOUS AGENTS IN COOPERATIVE MULTI-AGENT REINFORCEMENT LEARNING |
Qifeng Lin; Sun Yat-sen University |
Qing Ling; Sun Yat-sen University |
MLSP-27.3: SEMI-SUPERVISED BATCH ACTIVE LEARNING VIA BILEVEL OPTIMIZATION |
Zalán Borsos; ETH Zurich |
Marco Tagliasacchi; Google |
Andreas Krause; ETH Zurich |
MLSP-27.4: KERNEL-BASED LIFELONG POLICY GRADIENT REINFORCEMENT LEARNING |
Rami Mowakeaa; University of Maryland, Baltimore County |
Seung-Jun Kim; University of Maryland, Baltimore County |
Darren Emge; Combat Capabilities Development Command |
MLSP-27.5: POLICY AUGMENTATION: AN EXPLORATION STRATEGY FOR FASTER CONVERGENCE OF DEEP REINFORCEMENT LEARNING ALGORITHMS |
Arash Mahyari; Florida Institute For Human and Machine Cognition (IHMC) |
MLSP-27.6: GRAPHCOMM: A GRAPH NEURAL NETWORK BASED METHOD FOR MULTI-AGENT REINFORCEMENT LEARNING |
Siqi Shen; Xiamen University |
Yongquan Fu; National University of Defense Technology |
Huayou Su; National University of Defense Technology |
Hengyue Pan; National University of Defense Technology |
Qiao Peng; National University of Defense Technology |
Yong Dou; National University of Defense Technology |
Cheng Wang; Xiamen University |