Learning and Data Mining for Robotics Workshop

This workshop, collocated with the 19th European Conference on Machine Learning and the 12th Conference on Principles and Practice of Knowledge Discovery in Databases in Bled, Slovenia, aims at fostering research in Machine Learning and Data Mining applied to Robotics. All contributions related to

• Bayesian and probabilistic robotics,
• reinforcement learning and apprenticeship learning,
• learning from sensor data and logs (non exhaustive list)

are welcome. All contributions discussing issues such as:

• how to learn with/without a simulator, and how to face the reality gap
• how to build controllers that are robust with respect to motor/sensor failures
• how to derive self-driven criteria/goals for the robot
• how to deal with swarm robotics, distributed decision making and frugal communication,

Program Committee
Einoshin Suzuki	Chair	(Kyushu University, Japan)
Michèle Sebag	Chair	(CNRS & Université Paris-Sud, France)
Shin Ando		(Gunma University, Japan)
Jose L. Balcázar		(Technical University of Catalonia, Spain)
Aude Billard		(Ecole Polytechnique Fédérale de Lausanne, Switzerland)
Nicolas Bredèche		(Université Paris-Sud, France)
João Gama		(University of Porto, Portugal)
Peter Grünwald		(CWI, Netherlands)
Hitoshi Iba		(University of Tokyo, Japan)
Kristian Kersting		(Fraunhofer IAIS & University of Bonn, Germany)
Jan Peters		(Max Planck Institute for Biological Cybernetics, Germany)
Marc Schoenauer		(INRIA & Université Paris-Sud, France)
Marc Toussaint		(Technical University of Berlin, Germany)
Takashi Washio		(Osaka University, Japan)