idw – Informationsdienst Wissenschaft
Nachrichten, Termine, Experten
Nachrichten, Termine, Experten
We are pleased to announce our upcoming Distinguished Lecture Series talk by Jens Kober (TU Delft)! The talk will take place in person on March 5, in room UN32.101. Professor Kober will also be available for meetings on March 5. If you are interested in scheduling a meeting, please email ellis-office@uni-stuttgart.de.
Jens Kober is an associate professor at the TU Delft, Netherlands and an ELLIS Fellow. He worked as a postdoctoral scholar jointly at the CoR-Lab, Bielefeld University, Germany and at the Honda Research Institute Europe, Germany. He graduated in 2012 with a PhD Degree in Engineering from TU Darmstadt and the MPI for Intelligent Systems. For his research he received the annually awarded Georges Giralt PhD Award for the best PhD thesis in robotics in Europe, the 2018 IEEE RAS Early Academic Career Award, the 2022 RSS Early Career Award, and has received an ERC Starting grant. His research interests include motor skill learning, (deep) reinforcement learning, imitation learning, interactive learning, and machine learning for control.
Robots Learning Through Interactions
The acquisition and self-improvement of novel motor skills is among the most important problems in robotics. Complexity arises from interactions with their environment and humans, dealing with high-dimensional input data, non-linear dynamics in general and contacts in particular, multiple reference frames, and variability in objects, environments, tasks, and human behavior. A human teacher is always involved in the learning process, either directly (providing data) or indirectly (designing the optimization criterion), which raises the question: How to best make use of the interactions with the human teacher to render the learning process efficient and effective? In this talk I’ll argue that there are tremendous benefits in having a human teacher intermittently interact with a robot also while it is learning. I will discuss various methods we have developed in the fields of supervised learning, imitation learning, reinforcement learning, and interactive learning. All these concepts will be illustrated with benchmark tasks and real robot experiments ranging from fun (ball-in-a-cup) to more applied (retail environments).
Information on participating / attending:
No registration necessary.
Date:
03/05/2025 11:30 - 03/05/2025
Event venue:
Campus Vaihingen
Universitätstraße 32
Room 101101
70569 Stuttgart
Baden-Württemberg
Germany
Target group:
Journalists, Scientists and scholars
Email address:
Relevance:
regional
Subject areas:
Electrical engineering, Information technology, Mathematics
Types of events:
Presentation / colloquium / lecture
Entry:
02/25/2025
Sender/author:
Dina Schwedl
Department:
Stabsstelle Hochschulkommunikation
Event is free:
no
Language of the text:
English
URL of this event: http://idw-online.de/en/event78760
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