5 Jul - 2017 (Last edit: 2 Oct - 2017)
A Delft Robotics Institute sponsored Interdisciplinary Thematic Workshop.
Full information & Programme: http://ii.tudelft.nl/dwrl2017/
Workshop date: October 2nd, 2017.
Location: Mekelzaal 4 (MSB4), Science Centre Delft, Delft University of Technology.
Organizers: Joost Broekens (TU Delft), Jens Kober (TUD), Matthijs Spaan (TUD), Thomas Moerland (TUD).
Invited speakers: Guszti Eiben (Vrije Universiteit Amsterdam), Sven Behnke (Universitat Bonn), Sylvain Calinon (Idiap Research Institute), Frans Oliehoek (University of Liverpool).
Abstract
The aim of this one-day workshop is to gather scientist that are working
on the intersection of machine learning and robotics. Applications of
machine learning techniques in the robotic setting are strongly
increasing, e.g., in movement generation, in decision making, in
control, in vision, in perception, in design optimization, etc. At the
same time, high-impact machine learning publications seem to put
less-and-less emphasis at data efficiency. Thereby, these
implementations are hard to transfer to real-world robots, which can
only learn in wall-clock time and suffer from wear-and-tear. The goal of
this workshop is to identify the common themes and challenges in
learning techniques for robots, with researchers from a variety of robot
learning directions. We also encourage participation from non-robotic
machine learners (i.e. with work in simulation), when they are
interested in joining the discussion the long-term horizon for their
techniques in real-world applications.