[robotics-worldwide] [meetings] Call for Participation: ICRA Workshop on Machine Learning for Social Robotics, May 26th in Seattle

Shimon Whiteson shimon.whiteson at gmail.com
Fri May 1 14:01:34 PDT 2015

Call for Participation: Workshop on Machine Learning for Social Robotics
In conjunction with the International Conference on Robotics and Automation (ICRA)
May 26th 2015 (full day) in Seattle, Washington


Shimon Whiteson, University of Amsterdam
Ronald Poppe, Utrecht University
Vanessa Evers, University of Twente
Luis Merino, Pablo de Olavide University,
Stephen van Rump, Giraff Technologies


Social robots operate in a multi-modal world and are faced with increasingly complex tasks. These tasks have typically been addressed using hand-crafted knowledge and action rules. While initial progress has been made using this manual approach, it has its limitations with respect to generalisation, domain adaptation and efficiency. Fortunately, the vast amount of available data in combination with the increasing sophistication of machine learning techniques opens up possibilities for automatic learning in social robotics. 

In this workshop, we consider the unique challenges and opportunities that arise in developing machine learning techniques for social robotics. In particular, we consider two different scenarios in which humans and learning can interact in robotics. In the first, ``learning in the presence of humans", a robot must master a skill in an environment that contains humans. Typically, the task involves observing or interacting with those humans, including human-robot interaction and social navigation. In the second ``learning with humans in the loop", the task itself may not inherently involve humans but they are nonetheless involved in a teaching capacity during the learning process, e.g., via imitation learning, co-learning, or inverse reinforcement learning.

Machine learning challenges for social robotics can also be classified based on their focus on either perception or action. In perception-based tasks, the goal is to learn to understand something about the humans in the robot's environment, e.g., people detection and tracking, emotion recognition, human and social behaviour analysis, and social signal processing. In action-based tasks, the goal is to learn appropriate robot behaviour, e.g., socially normative navigation and body language.

Learning that involves humans also poses practical challenges for evaluation.  Much work remains to be done to establish metrics and facilitate rigorous comparisons.

Confirmed Invited Speakers:
Sonia Chernova: “Advancing interactive robot learning to real world domains and real world users".

Dizan Vasquez: “Planning based behavior modeling and learning for dynamic environments".

Andrea Thomaz: “Robots learning object-directed skills from human teachers”.

Further Information:
Up-to-date information about the workshop is available at http://bit.ly/1HA1Cp4

Please contact Shimon Whiteson (s.a.whiteson at uva.nl) with any questions.

Shimon Whiteson | Associate Professor
Intelligent Autonomous Systems Group
Informatics Institute | University of Amsterdam
Science Park 904 | 1098 XH Amsterdam
+31 (0)20.525.8701 | +31 (0)6.3851.0110

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