Reasoning with Latent Diffusion in Offline Reinforcement Learning

Offline reinforcement learning (RL) holds promise as a means to learn high-reward policies from a static dataset, without the need for further environment interactions. However, a key challenge in offline RL lies in effectively stitching portions of suboptimal trajectories from the static dataset wh...

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Bibliographic Details

Main Authors:	Venkatraman, Siddarth, Khaitan, Shivesh, Akella, Ravi Tej, Dolan, John, Schneider, Jeff, Berseth, Glen
Format:	Journal Article
Language:	English
Published:	12-09-2023
Subjects:	Computer Science - Learning
Online Access:	Get full text
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