Martin Riedmiller

Martin A. Riedmiller, Martin Riedmiller, 1998, 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227).

Human-level control through deep reinforcement learning

Shane Legg, Alex Graves, Marc G. Bellemare, 2015, Nature.

A direct adaptive method for faster backpropagation learning: the RPROP algorithm

Heinrich Braun, Martin Riedmiller, 1993, IEEE International Conference on Neural Networks.

Reinforcement learning in feedback control

Martin A. Riedmiller, Martin Riedmiller, Roland Hafner, 2011, Machine Learning.

Learning Robot Skill Embeddings

Karol Hausman, Jost Tobias Springenberg, Ziyu Wang, 2017, NIPS 2017.

Data-efficient Hindsight Off-policy Option Learning pdf

Dushyant Rao, Thomas Lampe, Abbas Abdolmaleki, 2020, ArXiv.

Lecture Notes in Artificial Intelligence (Subseries of Lecture NoteS in Computer Science): Preface

Martin A. Riedmiller, José Santos-Victor, Daniele Nardi, 2005 .

Quinoa: a Q-function You Infer Normalized Over Actions pdf

Abbas Abdolmaleki, Jost Tobias Springenberg, Nicolas Heess, 2019, ArXiv.

First results on the application of the Fynesse control architecture

Martin Spott, Martin A. Riedmiller, Martin Riedmiller, 1997, 1997 IEEE Aerospace Conference.

Creating a Robot Soccer Team from Scratch: the Brainstormers Tribots

Martin Lauer, Stefan Freitag, M. Fricke, 2003 .

Fuzzy-neuro-controlled verified instruction scheduler

Martin Spott, Martin A. Riedmiller, Thilo S. Gaul, 1999, 18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397).

Robust Reinforcement Learning for Continuous Control with Model Misspecification pdf

Nir Levine, Abbas Abdolmaleki, Jost Tobias Springenberg, 2020, ICLR.

Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning pdf

Thomas Lampe, Abbas Abdolmaleki, Jost Tobias Springenberg, 2020, ICLR.

V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control pdf

H. Francis Song, Abbas Abdolmaleki, Jost Tobias Springenberg, 2020, ICLR.

Advanced supervised learning in multi-layer perceptrons — From backpropagation to adaptive learning algorithms

Martin A. Riedmiller, Martin Riedmiller, 1994 .

Design of autonomously learning controllers using FYNESSE

Martin Spott, Martin A. Riedmiller, Martin Riedmiller, 2001 .

Local Search for Policy Iteration in Continuous Control pdf

Jackie Kay, Yuval Tassa, Jonas Buchli, 2020, ArXiv.

Learning by Experience from Others — Social Learning and Imitation in Animals and Robots

Martin A. Riedmiller, Martin Riedmiller, Artur Merke, 2003 .

Towards General and Autonomous Learning of Core Skills: A Case Study in Locomotion pdf

Martin Riedmiller, Markus Wulfmeier, Roland Hafner, 2020, ArXiv.

Rethinking Exploration for Sample-Efficient Policy Learning

Jost Tobias Springenberg, Martin Riedmiller, William F. Whitney, 2021 .

Rprop - Description and Implementation Details

Martin A. Riedmiller, Martin Riedmiller, 1994 .

A new method for the analysis of neural reference model control

Martin Riedmiller, Michael Wigbers, 1997, Proceedings of International Conference on Neural Networks (ICNN'97).

Representation Matters: Improving Perception and Exploration for Robotics pdf

Ankush Gupta, Thomas Lampe, Martin Riedmiller, 2020, ArXiv.

RPROP - A Fast Adaptive Learning Algorithm

Martin A. Riedmiller, Heinrich Braun, Martin Riedmiller, 1992 .

Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models

Thomas Lampe, Abbas Abdolmaleki, Jost Tobias Springenberg, 2019, CoRL.

Brainstormers 2003 - Team Description

Martin Riedmiller, Artur Merke, Daniel Withopf, 2003 .

Compositional Transfer in Hierarchical Reinforcement Learning

Thomas Lampe, Abbas Abdolmaleki, Jost Tobias Springenberg, 2019, RSS 2020.

Controlling an inverted pendulum by neural plant identification

Martin A. Riedmiller, Martin Riedmiller, 1993, Proceedings of IEEE Systems Man and Cybernetics Conference - SMC.

Simple Sensor Intentions for Exploration pdf

Jost Tobias Springenberg, Martin Riedmiller, Markus Wulfmeier, 2020, ArXiv.

Learning Symbolic Maps from Robot Navigation Bachelor Thesis in Cognitive Science

Martin A. Riedmiller, Ute Schmid, Martin Riedmiller, 2004 .

Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics

Martin A. Riedmiller, Thomas Lampe, Jonas Buchli, 2020, CoRL.

On Multi-objective Policy Optimization as a Tool for Reinforcement Learning pdf

Sandy H. Huang, Raia Hadsell, Abbas Abdolmaleki, 2021, ArXiv.

Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes pdf

Raia Hadsell, Claudio Fantacci, Francesco Nori, 2021, ArXiv.

Data-efficient Hindsight Off-policy Option Learning pdf

Dushyant Rao, Abbas Abdolmaleki, Nicolas Heess, 2021, ICML.

Evaluating model-based planning and planner amortization for continuous control pdf

Yuval Tassa, Alessandro Davide Ialongo, Abbas Abdolmaleki, 2021, ArXiv.

Collect & Infer - a fresh look at data-efficient Reinforcement Learning

Jost Tobias Springenberg, Nicolas Heess, Martin Riedmiller, 2021, CoRL.

Decoupled Exploration and Exploitation Policies for Sample-Efficient Reinforcement Learning

Kyunghyun Cho, Abbas Abdolmaleki, Jost Tobias Springenberg, 2021 .

Is Curiosity All You Need? On the Utility of Emergent Behaviours from Curious Exploration pdf

Nicolas Heess, Martin Riedmiller, Markus Wulfmeier, 2021, ArXiv.

Representation Matters: Improving Perception and Exploration for Robotics

Martin Riedmiller, Markus Wulfmeier, Roland Hafner, 2021, 2021 IEEE International Conference on Robotics and Automation (ICRA).

Is Bang-Bang Control All You Need? Solving Continuous Control with Bernoulli Policies pdf

Igor Gilitschenski, Martin A. Riedmiller, Daniela Rus, 2021, NeurIPS.

Speeding-up Reinforcement Learning with

Martin A. Riedmiller, Martin Riedmiller, 2001 .

Learning ( near ) Time Optimal Control for Flexible Robot Joints

Martin Riedmiller, 2011 .

On the Applicability of Unsupervised Feature Learning for Object Recognition in RGB-D Data

Martin A. Riedmiller, Jost Tobias Springenberg, Martin Riedmiller, 2011 .

Daily Prediction of the Foreign Exchange Rate Between the US Dollar and the German Mark Using Neural

Martin Riedmiller, Steffen Gutjahr, 1997 .