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insight - Skill-based Reinforcement Learning
Robust Policy Learning via Offline Skill Diffusion: DuSkill Framework
The author presents the DuSkill framework, utilizing offline skill diffusion with a guided diffusion model to enhance policy learning for tasks in different domains.
Robust Policy Learning via Offline Skill Diffusion: Bridging the Gap Between Datasets and Downstream Tasks in Different Domains
Offline skill diffusion framework enhances policy learning for tasks in different domains by generating diverse skills.
Robust Policy Learning via Offline Skill Diffusion: DuSkill Framework
DuSkill framework enhances policy learning by generating diverse skills for different domains.
Unsupervised Extraction of Transferable Robot Skills from Offline Data for Efficient Policy Learning
EXTRACT enables robots to efficiently learn new tasks by unsupervisedly extracting a discrete set of semantically meaningful, parameterized skills from offline data, which can be effectively leveraged for downstream reinforcement learning.
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