Martin Riedmiller

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Bio

My core scientific interest are intelligent machines, that are able to autonomously learn new things from scratch. I’m in particular interested in neural networks - a sort of mathematical model of the brain - and their ability to store and generalize information.

Research Interests

Papers共 245 篇Author StatisticsCo-AuthorSimilar Experts

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Learning from Negative Feedback, or Positive Feedback or Both

Abbas Abdolmaleki,Bilal Piot,Bobak Shahriari,Jost Springenberg,Tim Hertweck,Michael Bloesch,Rishabh Joshi,Thomas Lampe,Junhyuk Oh,Nicolas Heess,Jonas Buchli,Martin Riedmiller

ICLR 2025 (2025)

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DemoStart: Demonstration-led Auto-Curriculum Applied to Sim-to-real with Multi-Fingered Robots

Maria Bauza,Jose Enrique Chen,Valentin Dalibard,Nimrod Gileadi,Roland Hafner,Murilo F. Martins, Joss Moore,Rugile Pevceviciute,Antoine Laurens,Dushyant Rao,Martina Zambelli,Martin Riedmiller,Jon Scholz,Konstantinos Bousmalis,Francesco Nori,Nicolas Heess

CoRR (2024)

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Replay Across Experiments: A Natural Extension of Off-Policy RL

Dhruva Tirumala,Thomas Lampe,Jose Enrique Chen,Tuomas Haarnoja,Sandy Huang,Guy Lever,Ben Moran,Tim Hertweck,Leonard Hasenclever,Martin Riedmiller,Nicolas Heess,Markus Wulfmeier

ICLR 2024（2024）

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Game On: Towards Language Models As RL Experimenters

Jingwei Zhang,Thomas Lampe,Abbas Abdolmaleki,Jost Tobias Springenberg,Martin Riedmiller

CoRR (2024)

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Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning

Dhruva Tirumala,Markus Wulfmeier,Ben Moran,Sandy Huang,Jan Humplik,Guy Lever,Tuomas Haarnoja,Leonard Hasenclever,Arunkumar Byravan,Nathan Batchelor, Neil Sreendra, Kushal Patel, Marlon Gwira,Francesco Nori,Martin Riedmiller,Nicolas Heess

Conference on Robot Learning（2024）

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Real-World Fluid Directed Rigid Body Control Via Deep Reinforcement Learning

Mohak Bhardwaj,Thomas Lampe,Michael Neunert,Francesco Romano,Abbas Abdolmaleki,Arunkumar Byravan,Markus Wulfmeier,Martin Riedmiller,Jonas Buchli

6TH ANNUAL LEARNING FOR DYNAMICS & CONTROL CONFERENCE (2024): 414-427

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Imitating Language Via Scalable Inverse Reinforcement Learning

Markus Wulfmeier,Michael Bloesch,Nino Vieillard,Arun Ahuja,Jorg Bornschein,Sandy Huang,Artem Sokolov,Matt Barnes,Guillaume Desjardins,Alex Bewley,Sarah Maria Elisabeth Bechtle,Jost Tobias Springenberg,Nikola Momchev,Olivier Bachem,Matthieu Geist,Martin Riedmiller

NeurIPS 2024（2024）

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Offline Actor-Critic Reinforcement Learning Scales to Large Models

Jost Springenberg,Abbas Abdolmaleki,Jingwei Zhang,Oliver M Groth,Michael Bloesch,Thomas Lampe,Philemon Brakel,Sarah Bechtle,Steven Kapturowski,Roland Hafner,Nicolas Heess,Martin Riedmiller

ICML 2024 (2024)

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Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots

Lampe Thomas,Abdolmaleki Abbas,Huang Sandy H.,Bechtle Sarah,Springenberg Jost Tobias,Bloesch Michael,Groth Oliver,Hafner Roland,Hertweck Tim,Neunert Michael,Wulfmeier Markus,Zhang Jingwei,Nori Francesco,Heess Nicolas,Riedmiller Martin

ICRA 2024 (2024)

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Research Scientist

Papers共 245 篇Author StatisticsCo-AuthorSimilar Experts