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2020 – today
- 2022
[j5]Jonas Degrave
, Federico Felici, Jonas Buchli, Michael Neunert, Brendan D. Tracey, Francesco Carpanese, Timo Ewalds, Roland Hafner, Abbas Abdolmaleki, Diego de Las Casas, Craig Donner, Leslie Fritz, Cristian Galperti, Andrea Huber, James Keeling, Maria Tsimpoukelli, Jackie Kay, Antoine Merle, Jean-Marc Moret, Seb Noury, Federico Pesamosca, David Pfau, Olivier Sauter, Cristian Sommariva, Stefano Coda, Basil Duval, Ambrogio Fasoli, Pushmeet Kohli, Koray Kavukcuoglu, Demis Hassabis, Martin A. Riedmiller:
Magnetic control of tokamak plasmas through deep reinforcement learning. Nat. 602(7897): 414-419 (2022)- [i17]Steven Bohez, Saran Tunyasuvunakool, Philemon Brakel, Fereshteh Sadeghi, Leonard Hasenclever, Yuval Tassa, Emilio Parisotto, Jan Humplik, Tuomas Haarnoja, Roland Hafner, Markus Wulfmeier, Michael Neunert, Ben Moran, Noah Y. Siegel, Andrea Huber, Francesco Romano, Nathan Batchelor, Federico Casarini, Josh Merel, Raia Hadsell, Nicolas Heess:
Imitate and Repurpose: Learning Reusable Robot Movement Skills From Human and Animal Behaviors. CoRR abs/2203.17138 (2022) - [i16]Giulia Vezzani, Dhruva Tirumala, Markus Wulfmeier, Dushyant Rao, Abbas Abdolmaleki, Ben Moran, Tuomas Haarnoja, Jan Humplik, Roland Hafner, Michael Neunert, Claudio Fantacci, Tim Hertweck, Thomas Lampe, Fereshteh Sadeghi, Nicolas Heess, Martin A. Riedmiller:
SkillS: Adaptive Skill Sequencing for Efficient Temporally-Extended Exploration. CoRR abs/2211.13743 (2022) - 2021
- [c15]Michael Bloesch, Jan Humplik, Viorica Patraucean, Roland Hafner, Tuomas Haarnoja, Arunkumar Byravan, Noah Yamamoto Siegel, Saran Tunyasuvunakool, Federico Casarini, Nathan Batchelor, Francesco Romano, Stefano Saliceti, Martin A. Riedmiller, S. M. Ali Eslami, Nicolas Heess:
Towards Real Robot Learning in the Wild: A Case Study in Bipedal Locomotion. CoRL 2021: 1502-1511 - [c14]Martin A. Riedmiller, Jost Tobias Springenberg, Roland Hafner, Nicolas Heess:
Collect & Infer - a fresh look at data-efficient Reinforcement Learning. CoRL 2021: 1736-1744 - [c13]Markus Wulfmeier, Dushyant Rao, Roland Hafner, Thomas Lampe, Abbas Abdolmaleki, Tim Hertweck, Michael Neunert, Dhruva Tirumala, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller:
Data-efficient Hindsight Off-policy Option Learning. ICML 2021: 11340-11350 - [c12]Markus Wulfmeier, Arunkumar Byravan, Tim Hertweck, Irina Higgins, Ankush Gupta, Tejas Kulkarni, Malcolm Reynolds, Denis Teplyashin, Roland Hafner, Thomas Lampe, Martin A. Riedmiller:
Representation Matters: Improving Perception and Exploration for Robotics. ICRA 2021: 6512-6519 - [i15]Martin A. Riedmiller, Jost Tobias Springenberg, Roland Hafner, Nicolas Heess:
Collect & Infer - a fresh look at data-efficient Reinforcement Learning. CoRR abs/2108.10273 (2021) - [i14]Oliver Groth, Markus Wulfmeier, Giulia Vezzani, Vibhavari Dasagi, Tim Hertweck, Roland Hafner, Nicolas Heess, Martin A. Riedmiller:
Is Curiosity All You Need? On the Utility of Emergent Behaviours from Curious Exploration. CoRR abs/2109.08603 (2021) - 2020
- [c11]Roland Hafner, Tim Hertweck, Philipp Klöppner, Michael Bloesch, Michael Neunert, Markus Wulfmeier, Saran Tunyasuvunakool, Nicolas Heess, Martin A. Riedmiller:
Towards General and Autonomous Learning of Core Skills: A Case Study in Locomotion. CoRL 2020: 1084-1099 - [c10]Noah Y. Siegel, Jost Tobias Springenberg, Felix Berkenkamp, Abbas Abdolmaleki, Michael Neunert, Thomas Lampe, Roland Hafner, Nicolas Heess, Martin A. Riedmiller:
Keep Doing What Worked: Behavior Modelling Priors for Offline Reinforcement Learning. ICLR 2020 - [c9]Markus Wulfmeier, Abbas Abdolmaleki, Roland Hafner, Jost Tobias Springenberg, Michael Neunert, Noah Y. Siegel, Tim Hertweck, Thomas Lampe, Nicolas Heess, Martin A. Riedmiller:
Compositional Transfer in Hierarchical Reinforcement Learning. Robotics: Science and Systems 2020 - [i13]Michael Neunert, Abbas Abdolmaleki, Markus Wulfmeier, Thomas Lampe, Jost Tobias Springenberg, Roland Hafner, Francesco Romano, Jonas Buchli, Nicolas Heess, Martin A. Riedmiller:
Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics. CoRR abs/2001.00449 (2020) - [i12]Noah Y. Siegel, Jost Tobias Springenberg, Felix Berkenkamp, Abbas Abdolmaleki, Michael Neunert, Thomas Lampe, Roland Hafner, Nicolas Heess, Martin A. Riedmiller:
Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning. CoRR abs/2002.08396 (2020) - [i11]Tim Hertweck, Martin A. Riedmiller, Michael Bloesch, Jost Tobias Springenberg, Noah Y. Siegel, Markus Wulfmeier, Roland Hafner, Nicolas Heess:
Simple Sensor Intentions for Exploration. CoRR abs/2005.07541 (2020) - [i10]Markus Wulfmeier, Dushyant Rao, Roland Hafner, Thomas Lampe, Abbas Abdolmaleki, Tim Hertweck, Michael Neunert, Dhruva Tirumala, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller:
Data-efficient Hindsight Off-policy Option Learning. CoRR abs/2007.15588 (2020) - [i9]Roland Hafner, Tim Hertweck, Philipp Klöppner, Michael Bloesch, Michael Neunert, Markus Wulfmeier, Saran Tunyasuvunakool, Nicolas Heess, Martin A. Riedmiller:
Towards General and Autonomous Learning of Core Skills: A Case Study in Locomotion. CoRR abs/2008.12228 (2020) - [i8]Giulia Vezzani, Michael Neunert, Markus Wulfmeier, Rae Jeong, Thomas Lampe, Noah Y. Siegel, Roland Hafner, Abbas Abdolmaleki, Martin A. Riedmiller, Francesco Nori:
"What, not how": Solving an under-actuated insertion task from scratch. CoRR abs/2010.15492 (2020) - [i7]Markus Wulfmeier, Arunkumar Byravan, Tim Hertweck, Irina Higgins, Ankush Gupta, Tejas Kulkarni, Malcolm Reynolds, Denis Teplyashin, Roland Hafner, Thomas Lampe, Martin A. Riedmiller:
Representation Matters: Improving Perception and Exploration for Robotics. CoRR abs/2011.01758 (2020)
2010 – 2019
- 2019
- [c8]Arunkumar Byravan, Jost Tobias Springenberg, Abbas Abdolmaleki, Roland Hafner, Michael Neunert, Thomas Lampe, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller:
Imagined Value Gradients: Model-Based Policy Optimization with Tranferable Latent Dynamics Models. CoRL 2019: 566-589 - [c7]Michael Neunert, Abbas Abdolmaleki, Markus Wulfmeier, Thomas Lampe, Jost Tobias Springenberg, Roland Hafner, Francesco Romano, Jonas Buchli, Nicolas Heess, Martin A. Riedmiller:
Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics. CoRL 2019: 735-751 - [c6]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 - [i6]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) - [i5]Markus Wulfmeier, Abbas Abdolmaleki, Roland Hafner, Jost Tobias Springenberg, Michael Neunert, Tim Hertweck, Thomas Lampe, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller:
Regularized Hierarchical Policies for Compositional Transfer in Robotics. CoRR abs/1906.11228 (2019) - [i4]Arunkumar Byravan, Jost Tobias Springenberg, Abbas Abdolmaleki, Roland Hafner, Michael Neunert, Thomas Lampe, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller:
Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models. CoRR abs/1910.04142 (2019) - 2018
- [c5]Martin A. Riedmiller, Roland Hafner, Thomas Lampe, Michael Neunert, Jonas Degrave, Tom Van de Wiele, Vlad Mnih, Nicolas Heess, Jost Tobias Springenberg:
Learning by Playing Solving Sparse Reward Tasks from Scratch. ICML 2018: 4341-4350 - [i3]Martin A. Riedmiller, Roland Hafner, Thomas Lampe, Michael Neunert, Jonas Degrave, Tom Van de Wiele, Volodymyr Mnih, Nicolas Heess, Jost Tobias Springenberg:
Learning by Playing - Solving Sparse Reward Tasks from Scratch. CoRR abs/1802.10567 (2018) - 2017
- [i2]Ivaylo Popov, Nicolas Heess, Timothy P. Lillicrap, Roland Hafner, Gabriel Barth-Maron, Matej Vecerík, Thomas Lampe, Yuval Tassa, Tom Erez, Martin A. Riedmiller:
Data-efficient Deep Reinforcement Learning for Dexterous Manipulation. CoRR abs/1704.03073 (2017) - [i1]Rico Jonschkowski, Roland Hafner, Jonathan Scholz, Martin A. Riedmiller:
PVEs: Position-Velocity Encoders for Unsupervised Learning of Structured State Representations. CoRR abs/1705.09805 (2017) - 2011
- [j4]Roland Hafner, Martin A. Riedmiller:
Reinforcement learning in feedback control - Challenges and benchmarks from technical process control. Mach. Learn. 84(1-2): 137-169 (2011) - 2010
- [j3]Martin Lauer, Roland Hafner, Sascha Lange, Martin A. Riedmiller:
Cognitive concepts in autonomous soccer playing robots. Cogn. Syst. Res. 11(3): 287-309 (2010)
2000 – 2009
- 2009
- [j2]Martin A. Riedmiller, Thomas Gabel, Roland Hafner, Sascha Lange:
Reinforcement learning for robot soccer. Auton. Robots 27(1): 55-73 (2009) - 2008
- [c4]Martin A. Riedmiller, Roland Hafner, Sascha Lange, Martin Lauer:
Learning to dribble on a real robot by success and failure. ICRA 2008: 2207-2208 - 2007
- [c3]Roland Hafner, Martin A. Riedmiller:
Neural Reinforcement Learning Controllers for a Real Robot Application. ICRA 2007: 2098-2103 - [c2]Heiko Müller, Martin Lauer, Roland Hafner, Sascha Lange, Artur Merke, Martin A. Riedmiller:
Making a Robot Learn to Play Soccer Using Reward and Punishment. KI 2007: 220-234 - 2006
- [j1]Martin A. Riedmiller, Thomas Gabel, Roland Hafner, Sascha Lange, Martin Lauer:
Die Brainstormers: Entwurfsprinzipien lernfähiger autonomer Roboter. Inform. Spektrum 29(3): 175-190 (2006) - 2003
- [c1]Roland Hafner, Martin A. Riedmiller:
Reinforcement learning on an omnidirectional mobile robot. IROS 2003: 418-423
Coauthor Index
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