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Dueling Network Architectures for Deep Reinforcement Learning

Z. Wang, T. Schaul, M. Hessel, H. van Hasselt, M. Lanctot, and N. de Freitas. (2015)cite arxiv:1511.06581Comment: 15 pages, 5 figures, and 5 tables.

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Andreas Heßelmann

Peter Heßelmann

Benjamin Heßeler

Dominic Heßel

Michael Andreas Heßelmann

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Machine Learning for Parameter Screening in Computer Simulations.M. Hessel, F. Ortalli, and F. Borgatelli. MESAS, volume 8906 of Lecture Notes in Computer Science, page 308-320. Springer, (2014)Rainbow: Combining Improvements in Deep Reinforcement LearningM. Hessel, J. Modayil, H. van Hasselt, T. Schaul, G. Ostrovski, W. Dabney, D. Horgan, B. Piot, M. Azar, and D. Silver. (2017)cite arxiv:1710.02298Comment: Under review as a conference paper at AAAI 2018.Discovery of Options via Meta-Learned Subgoals.V. Veeriah, T. Zahavy, M. Hessel, Z. Xu, J. Oh, I. Kemaev, H. van Hasselt, D. Silver, and S. Singh. NeurIPS, page 29861-29873. (2021)Rainbow: Combining Improvements in Deep Reinforcement Learning.M. Hessel, J. Modayil, H. van Hasselt, T. Schaul, G. Ostrovski, W. Dabney, D. Horgan, B. Piot, M. Azar, and D. Silver. AAAI, page 3215-3222. AAAI Press, (2018)Automatic Tuning of Computational Models.M. Hessel, F. Ortalli, F. Borgatelli, and P. Lanzi. SIMULTECH (Selected Papers), volume 402 of Advances in Intelligent Systems and Computing, page 43-64. Springer, (2014)Learning by Directional Gradient Descent.D. Silver, A. Goyal, I. Danihelka, M. Hessel, and H. van Hasselt. ICLR, OpenReview.net, (2022)When to use parametric models in reinforcement learning?H. van Hasselt, M. Hessel, and J. Aslanides. NeurIPS, page 14322-14333. (2019)Discovery of Useful Questions as Auxiliary Tasks.V. Veeriah, M. Hessel, Z. Xu, J. Rajendran, R. Lewis, J. Oh, H. van Hasselt, D. Silver, and S. Singh. NeurIPS, page 9306-9317. (2019)The Predictron: End-To-End Learning and Planning.D. Silver, H. van Hasselt, M. Hessel, T. Schaul, A. Guez, T. Harley, G. Dulac-Arnold, D. Reichert, N. Rabinowitz, A. Barreto and 1 other author(s). ICML, volume 70 of Proceedings of Machine Learning Research, page 3191-3199. PMLR, (2017)What Can Learned Intrinsic Rewards Capture?Z. Zheng, J. Oh, M. Hessel, Z. Xu, M. Kroiss, H. van Hasselt, D. Silver, and S. Singh. CoRR, (2019)

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Disambiguation of "Hessel, Matteo"

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Dueling Network Architectures for Deep Reinforcement Learning

Please choose a person to relate this publication to

Andreas Heßelmann

Peter Heßelmann

Benjamin Heßeler

Dominic Heßel

Michael Andreas Heßelmann

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Hessel, Matteo"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Dueling Network Architectures for Deep Reinforcement Learning

Please choose a person to relate this publication to

Andreas Heßelmann

Peter Heßelmann

Benjamin Heßeler

Dominic Heßel

Michael Andreas Heßelmann

Other publications of authors with the same name

Disambiguation

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Dueling Network Architectures for Deep Reinforcement Learning