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2020 – today
- 2020
[b1]Devin Schwab:
Robot Deep Reinforcement Learning: Tensor State-Action Spaces and Auxiliary Task Learning with Multiple State Representations. Carnegie Mellon University, USA, 2020- [c6]Devin Schwab, Yifeng Zhu, Manuela Veloso:
Tensor Action Spaces for Multi-agent Robot Transfer Learning. IROS 2020: 5380-5386
2010 – 2019
- 2019
- [c5]Yifeng Zhu, Devin Schwab, Manuela Veloso:
Learning Primitive Skills for Mobile Robots. ICRA 2019: 7597-7603 - [c4]Devin Schwab, Jost Tobias Springenberg, Murilo Fernandes Martins, Michael Neunert, Thomas Lampe, Abbas Abdolmaleki, Tim Hertweck, Roland Hafner, Francesco Nori, Martin A. Riedmiller:
Simultaneously Learning Vision and Feature-Based Control Policies for Real-World Ball-In-A-Cup. Robotics: Science and Systems 2019 - [i1]Devin Schwab, Jost Tobias Springenberg, Murilo F. Martins, Thomas Lampe, Michael Neunert, Abbas Abdolmaleki, Tim Hertweck, Roland Hafner, Francesco Nori, Martin A. Riedmiller:
Simultaneously Learning Vision and Feature-based Control Policies for Real-world Ball-in-a-Cup. CoRR abs/1902.04706 (2019) - 2018
- [c3]Devin Schwab, Yifeng Zhu, Manuela M. Veloso:
Zero Shot Transfer Learning for Robot Soccer. AAMAS 2018: 2070-2072 - [c2]Devin Schwab, Yifeng Zhu, Manuela Veloso:
Learning Skills for Small Size League RoboCup. RoboCup 2018: 83-95 - 2017
- [j1]Devin Schwab
, Soumya Ray:
Offline reinforcement learning with task hierarchies. Mach. Learn. 106(9-10): 1569-1598 (2017) - 2012
- [c1]Robert Murawski, Kul Bhasin, David Bittner, Aaron Sweet, Rachel Coulter, Devin Schwab:
Hardware and software integration to support real-time space-link emulation. CAMAD 2012: 271-275
Coauthor Index
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