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Sequence Modeling is a Robust Contender for Offline Reinforcement Learning

P. Bhargava, R. Chitnis, A. Geramifard, S. Sodhani, and A. Zhang. (2023)cite arxiv:2305.14550.

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Reinforcement Learning of Multi-Domain Dialog Policies Via Action Embeddings.J. Mendez, A. Geramifard, M. Ghavamzadeh, and B. Liu. CoRR, (2022)UAV cooperative control with stochastic risk models.A. Geramifard, J. Redding, N. Roy, and J. How. ACC, page 3393-3398. IEEE, (2011)The Future of Artificially Intelligent Assistants.M. Muthukrishnan, A. Tomkins, L. Heck, A. Geramifard, and D. Agarwal. KDD, page 33-34. ACM, (2017)Biased Cost Pathfinding.A. Geramifard, P. Chubak, and V. Bulitko. AIIDE, page 112-114. The AAAI Press, (2006)Dyna-Style Planning with Linear Function Approximation and Prioritized Sweeping.R. Sutton, C. Szepesvári, A. Geramifard, and M. Bowling. UAI, page 528-536. AUAI Press, (2008)DialogStitch: Synthetic Deeper and Multi-Context Task-Oriented Dialogs.S. Kottur, C. Sankar, Z. Yu, and A. Geramifard. SIGDIAL, page 21-26. Association for Computational Linguistics, (2021)Domain-Independent turn-level Dialogue Quality Evaluation via User Satisfaction Estimation.P. Bodigutla, L. Wang, K. Ridgeway, J. Levy, S. Joshi, A. Geramifard, and S. Matsoukas. CoRR, (2019)RLPy: a value-function-based reinforcement learning framework for education and research.A. Geramifard, C. Dann, R. Klein, W. Dabney, and J. How. J. Mach. Learn. Res., (2015)Dyna-Style Planning with Linear Function Approximation and Prioritized SweepingR. Sutton, C. Szepesvári, A. Geramifard, and M. Bowling. CoRR, (2012)Online discovery of feature dependenciesA. Geramifard, J. Redding, J. How, F. Doshi, and N. Roy. International Conference on Machine Learning, page 881--888. (2011)

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Sequence Modeling is a Robust Contender for Offline Reinforcement Learning

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Disambiguation of "Geramifard, Alborz"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Sequence Modeling is a Robust Contender for Offline Reinforcement Learning

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Sequence Modeling is a Robust Contender for Offline Reinforcement Learning