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).

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.

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