NEWS MERL researcher Diego Romeres gave an invited talk at University of Connecticut on Reinforcement Learning for Robotics
Date released: November 22, 2019
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NEWS MERL researcher Diego Romeres gave an invited talk at University of Connecticut on Reinforcement Learning for Robotics Date:
November 20, 2019
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Description:
Diego Romeres, a Research Scientist in MERL's Data Analytics group, gave a seminar lecture at the Electrical and Computer Engineering Colloquium of the University of Connecticut. The talk described novel reinforcement algorithms based on combining physical models with non-parametric models of robotic systems derived from data.
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MERL Contact:
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Research Areas:
Artificial Intelligence, Data Analytics, Machine Learning, Robotics
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Related Publications
- "Quasi-Newton Trust Region Policy Optimization", Conference on Robot Learning (CoRL), Leslie Pack Kaelbling and Danica Kragic and Komei Sugiura, Eds., October 2019, pp. 945-954.
,BibTeX TR2019-120 PDF Software- @inproceedings{Jha2019oct,
- author = {Jha, Devesh K. and Raghunathan, Arvind and Romeres, Diego},
- title = {Quasi-Newton Trust Region Policy Optimization},
- booktitle = {Conference on Robot Learning (CoRL)},
- year = 2019,
- editor = {Leslie Pack Kaelbling and Danica Kragic and Komei Sugiura},
- pages = {945--954},
- month = oct,
- publisher = {Proceedings of Machine Learning Research},
- url = {https://www.merl.com/publications/TR2019-120}
- }
- "Semiparametrical Gaussian Processes Learning of Forward Dynamical Models for Navigating in a Circular Maze", IEEE International Conference on Robotics and Automation (ICRA), DOI: 10.1109/ICRA.2019.8794229, May 2019, pp. 3195-3202.
,BibTeX TR2019-028 PDF Video Software- @inproceedings{Romeres2019may,
- author = {Romeres, Diego and Jha, Devesh K. and Dalla Libera, Alberto and Yerazunis, William S. and Nikovski, Daniel N.},
- title = {Semiparametrical Gaussian Processes Learning of Forward Dynamical Models for Navigating in a Circular Maze},
- booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
- year = 2019,
- pages = {3195--3202},
- month = may,
- publisher = {IEEE},
- doi = {10.1109/ICRA.2019.8794229},
- issn = {2577-087X},
- isbn = {978-1-5386-6027-0},
- url = {https://www.merl.com/publications/TR2019-028}
- }
- "Quasi-Newton Trust Region Policy Optimization", Conference on Robot Learning (CoRL), Leslie Pack Kaelbling and Danica Kragic and Komei Sugiura, Eds., October 2019, pp. 945-954.
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