by Daniel Jost, Basavasagar Patil, Xavier Alameda-Pineda, and Chris Reinke [preprint] | [code] Abstract: Deep Neural Networks (DNNs) became the standard tool for function approximation with most of the introduced architectures being developed for high-dimensional input data. However, many real-world problems have low-dimensional inputs for which the standard Multi-Layer Perceptron…
The internship aims to explore the usefulness of the Fisher-Ráo metric combined with deep probabilistic models.
The internship aims to develop a controller for a social mobile robot (ARI) to have a conversation with people using large language models (LLMs) such as ChatGPT.
by Chris Reinke and Xavier Alameda-Pineda Transactions on Machine Learning Research [Paper][Code] Abstract. Transfer in Reinforcement Learning aims to improve learning performance on target tasks using knowledge from experienced source tasks. Successor features (SF) are a prominent transfer mechanism in domains where the reward function changes between tasks. They reevaluate…
Project We are surrounded by dynamic and complex systems ranging from the formation process of galaxies to production systems, such as for the synthesis of medical drugs. Exploring these systems in simulation or by experiment helps us to understand them and to discover new and interesting behaviors and outcomes. This…
Project The internship is part of our research project into Deep Reinforcement Learning (DRL) [1,2] for the European SPRING project [3]. SPRING aims to develop control mechanisms for humanoid robots [4] that will be employed in health care environments. The robots should communicate with patients, their families, and caretakers to…
Topic: The internship is part of our research project into Deep Reinforcement Learning (DRL) [1] for the European SPRING project. SPRING aims to develop control mechanisms for mobile robots that will be employed in hospitals and health care environments. The robots should communicate with elderly people, their families and caretakers…
