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Martin A. Riedmiller
- > Home > Persons > Martin A. Riedmiller
Publications
- 2024
- [i58]Jost Tobias Springenberg, Abbas Abdolmaleki, Jingwei Zhang, Oliver Groth, Michael Bloesch, Thomas Lampe, Philemon Brakel, Sarah Bechtle, Steven Kapturowski, Roland Hafner, Nicolas Heess, Martin A. Riedmiller:
Offline Actor-Critic Reinforcement Learning Scales to Large Models. CoRR abs/2402.05546 (2024) - 2023
- [i56]Jingwei Zhang, Jost Tobias Springenberg, Arunkumar Byravan, Leonard Hasenclever, Abbas Abdolmaleki, Dushyant Rao, Nicolas Heess, Martin A. Riedmiller:
Leveraging Jumpy Models for Planning and Fast Learning in Robotic Domains. CoRR abs/2302.12617 (2023) - [i55]Ingmar Schubert, Jingwei Zhang, Jake Bruce, Sarah Bechtle, Emilio Parisotto, Martin A. Riedmiller, Jost Tobias Springenberg, Arunkumar Byravan, Leonard Hasenclever, Nicolas Heess:
A Generalist Dynamics Model for Control. CoRR abs/2305.10912 (2023) - [i54]Konstantinos Bousmalis, Giulia Vezzani, Dushyant Rao, Coline Devin, Alex X. Lee, Maria Bauzá, Todor Davchev, Yuxiang Zhou, Agrim Gupta, Akhil Raju, Antoine Laurens, Claudio Fantacci, Valentin Dalibard, Martina Zambelli, Murilo F. Martins, Rugile Pevceviciute, Michiel Blokzijl, Misha Denil, Nathan Batchelor, Thomas Lampe, Emilio Parisotto, Konrad Zolna, Scott E. Reed, Sergio Gómez Colmenarejo, Jon Scholz, Abbas Abdolmaleki, Oliver Groth, Jean-Baptiste Regli, Oleg Sushkov, Thomas Rothörl, Jose Enrique Chen, Yusuf Aytar, Dave Barker, Joy Ortiz, Martin A. Riedmiller, Jost Tobias Springenberg, Raia Hadsell, Francesco Nori, Nicolas Heess:
RoboCat: A Self-Improving Foundation Agent for Robotic Manipulation. CoRR abs/2306.11706 (2023) - [i53]Norman Di Palo, Arunkumar Byravan, Leonard Hasenclever, Markus Wulfmeier, Nicolas Heess, Martin A. Riedmiller:
Towards A Unified Agent with Foundation Models. CoRR abs/2307.09668 (2023) - [i50]Shruti Mishra, Ankit Anand, Jordan Hoffmann, Nicolas Heess, Martin A. Riedmiller, Abbas Abdolmaleki, Doina Precup:
Policy composition in reinforcement learning via multi-objective policy optimization. CoRR abs/2308.15470 (2023) - [i48]Dhruva Tirumala, Thomas Lampe, Jose Enrique Chen, Tuomas Haarnoja, Sandy H. Huang, Guy Lever, Ben Moran, Tim Hertweck, Leonard Hasenclever, Martin A. Riedmiller, Nicolas Heess, Markus Wulfmeier:
Replay across Experiments: A Natural Extension of Off-Policy RL. CoRR abs/2311.15951 (2023) - [i46]Thomas Lampe, Abbas Abdolmaleki, Sarah Bechtle, Sandy H. Huang, Jost Tobias Springenberg, Michael Bloesch, Oliver Groth, Roland Hafner, Tim Hertweck, Michael Neunert, Markus Wulfmeier, Jingwei Zhang, Francesco Nori, Nicolas Heess, Martin A. Riedmiller:
Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots. CoRR abs/2312.11374 (2023) - 2022
- [c101]Sasha Salter, Markus Wulfmeier, Dhruva Tirumala, Nicolas Heess, Martin A. Riedmiller, Raia Hadsell, Dushyant Rao:
MO2: Model-Based Offline Options. CoLLAs 2022: 902-919 - [c100]Arunkumar Byravan, Leonard Hasenclever, Piotr Trochim, Mehdi Mirza, Alessandro Davide Ialongo, Yuval Tassa, Jost Tobias Springenberg, Abbas Abdolmaleki, Nicolas Heess, Josh Merel, Martin A. Riedmiller:
Evaluating Model-Based Planning and Planner Amortization for Continuous Control. ICLR 2022 - [i44]Bobak Shahriari, Abbas Abdolmaleki, Arunkumar Byravan, Abe Friesen, Siqi Liu, Jost Tobias Springenberg, Nicolas Heess, Matt Hoffman, Martin A. Riedmiller:
Revisiting Gaussian mixture critics in off-policy reinforcement learning: a sample-based approach. CoRR abs/2204.10256 (2022) - [i43]Sasha Salter, Markus Wulfmeier, Dhruva Tirumala, Nicolas Heess, Martin A. Riedmiller, Raia Hadsell, Dushyant Rao:
MO2: Model-Based Offline Options. CoRR abs/2209.01947 (2022) - [i41]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
- [c99]Sandy H. Huang, Abbas Abdolmaleki, Giulia Vezzani, Philemon Brakel, Daniel J. Mankowitz, Michael Neunert, Steven Bohez, Yuval Tassa, Nicolas Heess, Martin A. Riedmiller, Raia Hadsell:
A Constrained Multi-Objective Reinforcement Learning Framework. CoRL 2021: 883-893 - [c97]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 - [c96]Martin A. Riedmiller, Jost Tobias Springenberg, Roland Hafner, Nicolas Heess:
Collect & Infer - a fresh look at data-efficient Reinforcement Learning. CoRL 2021: 1736-1744 - [c95]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 - [i39]Abbas Abdolmaleki, Sandy H. Huang, Giulia Vezzani, Bobak Shahriari, Jost Tobias Springenberg, Shruti Mishra, Dhruva TB, Arunkumar Byravan, Konstantinos Bousmalis, András György, Csaba Szepesvári, Raia Hadsell, Nicolas Heess, Martin A. Riedmiller:
On Multi-objective Policy Optimization as a Tool for Reinforcement Learning. CoRR abs/2106.08199 (2021) - [i38]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) - [i37]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) - [i36]Arunkumar Byravan, Leonard Hasenclever, Piotr Trochim, Mehdi Mirza, Alessandro Davide Ialongo, Yuval Tassa, Jost Tobias Springenberg, Abbas Abdolmaleki, Nicolas Heess, Josh Merel, Martin A. Riedmiller:
Evaluating model-based planning and planner amortization for continuous control. CoRR abs/2110.03363 (2021) - 2020
- [c91]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 - [c89]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 - [c88]H. Francis Song, Abbas Abdolmaleki, Jost Tobias Springenberg, Aidan Clark, Hubert Soyer, Jack W. Rae, Seb Noury, Arun Ahuja, Siqi Liu, Dhruva Tirumala, Nicolas Heess, Dan Belov, Martin A. Riedmiller, Matthew M. Botvinick:
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control. ICLR 2020 - [c87]Abbas Abdolmaleki, Sandy H. Huang, Leonard Hasenclever, Michael Neunert, H. Francis Song, Martina Zambelli, Murilo F. Martins, Nicolas Heess, Raia Hadsell, Martin A. Riedmiller:
A distributional view on multi-objective policy optimization. ICML 2020: 11-22 - [c86]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 - [i33]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) - [i32]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) - [i31]Abbas Abdolmaleki, Sandy H. Huang, Leonard Hasenclever, Michael Neunert, H. Francis Song, Martina Zambelli, Murilo F. Martins, Nicolas Heess, Raia Hadsell, Martin A. Riedmiller:
A Distributional View on Multi-Objective Policy Optimization. CoRR abs/2005.07513 (2020) - [i30]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) - [i29]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) - [i28]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) - [i27]Jost Tobias Springenberg, Nicolas Heess, Daniel J. Mankowitz, Josh Merel, Arunkumar Byravan, Abbas Abdolmaleki, Jackie Kay, Jonas Degrave, Julian Schrittwieser, Yuval Tassa, Jonas Buchli, Dan Belov, Martin A. Riedmiller:
Local Search for Policy Iteration in Continuous Control. CoRR abs/2010.05545 (2020) - [i26]Daniel J. Mankowitz, Dan A. Calian, Rae Jeong, Cosmin Paduraru, Nicolas Heess, Sumanth Dathathri, Martin A. Riedmiller, Timothy A. Mann:
Robust Constrained Reinforcement Learning for Continuous Control with Model Misspecification. CoRR abs/2010.10644 (2020) - 2019
- [c85]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 - [c84]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 - [i23]Carlos Florensa, Jonas Degrave, Nicolas Heess, Jost Tobias Springenberg, Martin A. Riedmiller:
Self-supervised Learning of Image Embedding for Continuous Control. CoRR abs/1901.00943 (2019) - [i20]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) - [i19]H. Francis Song, Abbas Abdolmaleki, Jost Tobias Springenberg, Aidan Clark, Hubert Soyer, Jack W. Rae, Seb Noury, Arun Ahuja, Siqi Liu, Dhruva Tirumala, Nicolas Heess, Dan Belov, Martin A. Riedmiller, Matthew M. Botvinick:
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control. CoRR abs/1909.12238 (2019) - [i18]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) - [i17]Jonas Degrave, Abbas Abdolmaleki, Jost Tobias Springenberg, Nicolas Heess, Martin A. Riedmiller:
Quinoa: a Q-function You Infer Normalized Over Actions. CoRR abs/1911.01831 (2019) - 2018
- [c81]Abbas Abdolmaleki, Jost Tobias Springenberg, Yuval Tassa, Rémi Munos, Nicolas Heess, Martin A. Riedmiller:
Maximum a Posteriori Policy Optimisation. ICLR (Poster) 2018 - [c80]Karol Hausman, Jost Tobias Springenberg, Ziyu Wang, Nicolas Heess, Martin A. Riedmiller:
Learning an Embedding Space for Transferable Robot Skills. ICLR (Poster) 2018 - [c79]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 - [c78]Alvaro Sanchez-Gonzalez, Nicolas Heess, Jost Tobias Springenberg, Josh Merel, Martin A. Riedmiller, Raia Hadsell, Peter W. Battaglia:
Graph Networks as Learnable Physics Engines for Inference and Control. ICML 2018: 4467-4476 - [i15]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) - [i14]Alvaro Sanchez-Gonzalez, Nicolas Heess, Jost Tobias Springenberg, Josh Merel, Martin A. Riedmiller, Raia Hadsell, Peter W. Battaglia:
Graph networks as learnable physics engines for inference and control. CoRR abs/1806.01242 (2018) - [i13]Abbas Abdolmaleki, Jost Tobias Springenberg, Yuval Tassa, Rémi Munos, Nicolas Heess, Martin A. Riedmiller:
Maximum a Posteriori Policy Optimisation. CoRR abs/1806.06920 (2018) - [i12]Abbas Abdolmaleki, Jost Tobias Springenberg, Jonas Degrave, Steven Bohez, Yuval Tassa, Dan Belov, Nicolas Heess, Martin A. Riedmiller:
Relative Entropy Regularized Policy Iteration. CoRR abs/1812.02256 (2018) - 2017
- [i11]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) - [i9]Nicolas Heess, Dhruva TB, Srinivasan Sriram, Jay Lemmon, Josh Merel, Greg Wayne, Yuval Tassa, Tom Erez, Ziyu Wang, S. M. Ali Eslami, Martin A. Riedmiller, David Silver:
Emergence of Locomotion Behaviours in Rich Environments. CoRR abs/1707.02286 (2017) - [i8]Matej Vecerík, Todd Hester, Jonathan Scholz, Fumin Wang, Olivier Pietquin, Bilal Piot, Nicolas Heess, Thomas Rothörl, Thomas Lampe, Martin A. Riedmiller:
Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards. CoRR abs/1707.08817 (2017) - 2016
- [i7]Nicolas Heess, Gregory Wayne, Yuval Tassa, Timothy P. Lillicrap, Martin A. Riedmiller, David Silver:
Learning and Transfer of Modulated Locomotor Controllers. CoRR abs/1610.05182 (2016) - 2014
- [c73]David Silver, Guy Lever, Nicolas Heess, Thomas Degris, Daan Wierstra, Martin A. Riedmiller:
Deterministic Policy Gradient Algorithms. ICML 2014: 387-395
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