3 papers
cs.AI2024
Efficient Adaptation in Mixed-Motive Environments via Hierarchical Opponent Modeling and Planning
Yizhe Huang, Anji Liu, Fanqi Kong +3
Despite the recent successes of multi-agent reinforcement learning (MARL) algorithms, efficiently adapting to co-players in mixed-motive environments remains a significant challeng…
cs.CL2024
Combining Supervised Learning and Reinforcement Learning for Multi-Label Classification Tasks with Partial Labels
Zixia Jia, Junpeng Li, Shichuan Zhang +2
Traditional supervised learning heavily relies on human-annotated datasets, especially in data-hungry neural approaches. However, various tasks, especially multi-label tasks like d…
cs.RO2024
Smart Help: Strategic Opponent Modeling for Proactive and Adaptive Robot Assistance in Households
Zhihao Cao, Zidong Wang, Siwen Xie +2
Despite the significant demand for assistive technology among vulnerable groups (e.g., the elderly, children, and the disabled) in daily tasks, research into advanced AI-driven ass…