no code implementations • 12 Apr 2024 • Nicolai Dorka, Janusz Marecki, Ammar Anwar
Addressing the challenge of a digital assistant capable of executing a wide array of user tasks, our research focuses on the realm of instruction-based mobile device control.
no code implementations • 21 Mar 2023 • Johan Vertens, Nicolai Dorka, Tim Welschehold, Michael Thompson, Wolfram Burgard
By training everything end-to-end with the loss of the dynamics model, we enforce the latent mapper to learn an update rule for the latent map that is useful for the subsequent dynamics model.
1 code implementation • 17 Mar 2023 • Nicolai Dorka, Tim Welschehold, Wolfram Burgard
Early stopping based on the validation set performance is a popular approach to find the right balance between under- and overfitting in the context of supervised learning.
Model-based Reinforcement Learning reinforcement-learning +1
1 code implementation • 24 Nov 2021 • Nicolai Dorka, Tim Welschehold, Joschka Boedecker, Wolfram Burgard
Accurate value estimates are important for off-policy reinforcement learning.
no code implementations • 17 Nov 2020 • Nicolai Dorka, Johannes Meyer, Wolfram Burgard
Real-time object detection in videos using lightweight hardware is a crucial component of many robotic tasks.
1 code implementation • 6 Jul 2020 • Artemij Amiranashvili, Nicolai Dorka, Wolfram Burgard, Vladlen Koltun, Thomas Brox
Imitation learning is a powerful family of techniques for learning sensorimotor coordination in immersive environments.
no code implementations • 18 Mar 2019 • Jingwei Zhang, Niklas Wetzel, Nicolai Dorka, Joschka Boedecker, Wolfram Burgard
Many state-of-the-art methods use intrinsic motivation to complement the sparse extrinsic reward signal, giving the agent more opportunities to receive feedback during exploration.