Diffusion Policies for Out-of-Distribution Generalization in Offline Reinforcement Learning-Reference-Cited by-同舟云学术

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Diffusion Policies for Out-of-Distribution Generalization in Offline Reinforcement Learning

Published:2024-04 Issue:4 Volume:9 Page:3116-3123
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Ada Suzan Ece¹^ORCID,Oztop Erhan²^ORCID,Ugur Emre¹^ORCID

Affiliation:

1. Department of Computer Engineering, Bogazici University, Istanbul, Türkiye

2. SISReC, OTRI, Osaka University, Osaka, Japan

Funder

JSPS KAKENHI

New Energy and Industrial Technology Development Organization

Türkiye Bilimsel ve Teknolojik Araştırma Kurumu

European Commission

INVERSE Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7083369/10440130/10423845.pdf?arnumber=10423845

Reference43 articles.

1. D4rl: Datasets for deep data-driven reinforcement learning;Fu,2020

2. Offline reinforcement learning: Tutorial, review, and perspectives on open problems;Levine,2020

3. Dealing with the unknown: Pessimistic offline reinforcement learning;Li,2021

4. Diffusion policy: Visuomotor policy learning via action diffusion;Chi

5. Implicit behavioral cloning;Florence,2021

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