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Sequence Modeling is a Robust Contender for Offline Reinforcement Learning

, , , , и . (2023)cite arxiv:2305.14550.

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Rohan Karande

Ali Reza Rohani-Dezfuli

Massoud Rohani

Rohan Karande

Gunawarna Rohan Fernando

 

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Learning Efficient Abstract Planning Models that Choose What to Predict., , , , , и . CoRL, том 229 из Proceedings of Machine Learning Research, стр. 2070-2095. PMLR, (2023)Learning Neuro-Symbolic Relational Transition Models for Bilevel Planning., , , , и . CoRR, (2021)Towards Optimal Correlational Object Search., , , , и . ICRA, стр. 7313-7319. IEEE, (2022)Finding Frequent Entities in Continuous Data., , , и . IJCAI, стр. 1992-1999. ijcai.org, (2018)Learning Neuro-Symbolic Relational Transition Models for Bilevel Planning., , , , и . IROS, стр. 4166-4173. IEEE, (2022)Planning with Learned Object Importance in Large Problem Instances using Graph Neural Networks., , , , , и . AAAI, стр. 11962-11971. AAAI Press, (2021)Predicate Invention for Bilevel Planning., , , , , , и . AAAI, стр. 12120-12129. AAAI Press, (2023)IQL-TD-MPC: Implicit Q-Learning for Hierarchical Model Predictive Control., , , , , , и . ICRA, стр. 9154-9160. IEEE, (2024)Learning What Information to Give in Partially Observed Domains., , и . CoRL, том 87 из Proceedings of Machine Learning Research, стр. 724-733. PMLR, (2018)Planning to Give Information in Partially Observed Domains with a Learned Weighted Entropy Model., , и . CoRR, (2018)