4 citations · 5 across the 22 of their papers we have counts for
Showing cs.AIShow all
2 papers · 1 filter
cs.AI2026
Knowledge Reutilization in Meta-Reinforcement Learning
Yuan Meng, Bo Wang, Juan de los Rios Ruiz +4
Meta-reinforcement learning enables fast adaptation by extracting shared structure from related tasks, but existing end-to-end methods often couple task inference with embodiment-s…
cs.AI2022★ 1 cited
Learning from Symmetry: Meta-Reinforcement Learning with Symmetrical Behaviors and Language Instructions
Xiangtong Yao, Zhenshan Bing, Genghang Zhuang +4
Meta-reinforcement learning (meta-RL) is a promising approach that enables the agent to learn new tasks quickly. However, most meta-RL algorithms show poor generalization in multi-…