Michael Lutter

According to our database, Michael Lutter authored at least 20 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Continuous-Time Fitted Value Iteration for Robust Policies.

Michael Lutter, Boris Belousov, Shie Mannor, Dieter Fox, Animesh Garg, Jan Peters

IEEE Trans. Pattern Anal. Mach. Intell., May, 2023

Combining physics and deep learning to learn continuous-time dynamics models.

Michael Lutter, Jan Peters

Int. J. Robotics Res., March, 2023

Inductive Biases in Machine Learning for Robotics and Control

Michael Lutter

Springer Tracts in Advanced Robotics 156, Springer, ISBN: 978-3-031-37831-7, 2023

Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning.

Daniel Palenicek, Michael Lutter, Joao Carvalho, Jan Peters

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Revisiting Model-based Value Expansion.

Daniel Palenicek, Michael Lutter, Jan Peters

CoRR, 2022

2021

Inductive Biases in Machine Learning for Robotics and Control

Michael Lutter

PhD thesis, 2021

A Differentiable Newton-Euler Algorithm for Real-World Robotics.

Michael Lutter, Johannes Silberbauer, Joe Watson, Jan Peters

CoRR, 2021

Learning Dynamics Models for Model Predictive Agents.

Michael Lutter, Leonard Hasenclever, Arunkumar Byravan, Gabriel Dulac-Arnold, Piotr Trochim, Nicolas Heess, Josh Merel, Yuval Tassa

CoRR, 2021

Robust Value Iteration for Continuous Control Tasks.

Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg

Proceedings of the Robotics: Science and Systems XVII, Virtual Event, July 12-16, 2021., 2021

Differentiable Physics Models for Real-world Offline Model-based Reinforcement Learning.

Michael Lutter, Johannes Silberbauer, Joe Watson, Jan Peters

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Value Iteration in Continuous Actions, States and Time.

Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg

Proceedings of the 38th International Conference on Machine Learning, 2021

Building Skill Learning Systems for Robotics.

Michael Lutter, Debora Clever, René Kirsten, Kim Listmann, Jan Peters

Proceedings of the 17th IEEE International Conference on Automation Science and Engineering, 2021

Trajectory Optimization of Energy Consumption and Expected Service Life of a Robotic System.

Florian Stuhlenmiller, Debora Clever, Stephan Rinderknecht, Michael Lutter, Jan Peters

Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2021

2020

Incremental Learning of an Open-Ended Collaborative Skill Library.

Dorothea Koert, Susanne Trick, Marco Ewerton, Michael Lutter, Jan Peters

Int. J. Humanoid Robotics, 2020

A Differentiable Newton Euler Algorithm for Multi-body Model Learning.

Michael Lutter, Johannes Silberbauer, Joe Watson, Jan Peters

CoRR, 2020

High Acceleration Reinforcement Learning for Real-World Juggling with Binary Rewards.

Kai Ploeger, Michael Lutter, Jan Peters

Proceedings of the 4th Conference on Robot Learning, 2020

2019

Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems.

Michael Lutter, Kim Listmann, Jan Peters

Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning.

Michael Lutter, Christian Ritter, Jan Peters

Proceedings of the 7th International Conference on Learning Representations, 2019

HJB Optimal Feedback Control with Deep Differential Value Functions and Action Constraints.

Michael Lutter, Boris Belousov, Kim Listmann, Debora Clever, Jan Peters

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

2018

Online Learning of an Open-Ended Skill Library for Collaborative Tasks.

Dorothea Koert, Susanne Trick, Marco Ewerton, Michael Lutter, Jan Peters

Proceedings of the 18th IEEE-RAS International Conference on Humanoid Robots, 2018