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* Proceedings published in the ACM digital library *
* Four internationally renowned invited speakers *
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Intelligent systems or robots that interact with their environment by perceiving, acting or communicating often face a challenge in how to bring these different concepts together. One of the main reasons for this challenge is the fact that the core concepts in perception, action and communication are typically studied by different communities: the computer vision, robotics and natural language processing communities, among others, without much interchange between them. As machine learning lies at the core of these communities, it can act as a unifying factor in bringing the communities closer together. Unifying these communities is highly important for understanding how state-of-the-art approaches from different disciplines can be combined (and applied) to form generally interactive intelligent systems.

The goal of this workshop is to bring researchers from multiple disciplines together who are in one way or another affected by the gap between action, perception and communication that typically exists for interactive systems or robots. Topics of interest include, but are not limited to:

Machine Learning:
• Reinforcement Learning
• Supervised Learning
• Unsupervised Learning
• Semi-Supervised Learning
• Active Learning
• Learning from human feedback
• Learning from teaching, tutoring, instruction and demonstration
•Combinations or generalisations of the above

Interactive Systems:
• (Socially) Interactive Robotics
• Embodied Virtual Agents
• Avatars
• Multimodal systems
• Cognitive (robotics) architectures

Types of Communication:
• System interacting with a single human user
• System interacting with multiple human users
• System interacting with the environment
• System interacting with other machines

Example applications could include: (1) a robot may learn to coordinate its speech with its actions, taking into account visual feedback during their execution; (2) an autonomous car may learn to coordinate its acceleration and steering behaviours depending on observations of obstacles; (3) a team of robots playing soccer may learn to coordinate their ball kicks depending on the dynamic locations of their opponents; (4) a sensorimotor system may learn to drive a wheelchair through feedback from visual signals of the environment; (5) a mobile robot may interactively learn from human guidance how to manipulate objects and move through a building, based on human feedback using language, gestures and interactive dialogue; or (6) a multimodal smart phone can adapt its input and output modalities to the user's goals, workload and surroundings.

Submission website: https://www.easychair.org/conferences/?conf=mlis2013.

Submissions can take two forms. Long papers should not exceed 8 pages, and short (position) papers should not exceed 4 pages. They should follow the ACM SIG proceedings format (option 1): http://www.acm.org/sigs/publications/proceedings-templates. All submissions should be anonymised for peer-review.

Accepted papers will be published by ACM International Conference Proceedings Series under ISBN 978-1-4503-2019-1. The proceedings of MLIS’13 will be available on the ACM digital library on the day of the workshop.

Invited Speakers:
Prof. Dr. Martin Riedmiller, University of Freiburg, Germany
Talk: "Learning Machines that Perceive, Act and Communicate"
Prof. Dr. Olivier Pietquin, Supélec, France
Talk: "Inverse Reinforcement Learning for Interactive Systems"
Dr. George Konidaris, MIT, United States
Title: "Autonomous Robot Skill Acquisition"
Dr. Jean Christophe Baillie, Aldebaran Robotics
Title: "Developmental Robotics at Aldebaran A-Lab"

Important Dates:
April 20, Paper submission deadline (Hawaii Time)
May 20, Notification of acceptance
June 16, Camera-ready deadline
August 4, MLIS workshop

Organising Committee:
Heriberto Cuayáhuitl, Heriot-Watt University, Edinburgh, UK
Lutz Frommberger, University of Bremen, Germany
Nina Dethlefs, Heriot-Watt University, Edinburgh, UK
Martijn van Otterlo, Radboud University Nijmegen, The Netherlands

Programme Committee:
Kai Arras, University of Freiburg, Germany
Maren Bennewitz, University of Freiburg, Germany
Dan Bohus, Microsoft Research, USA
Martin Butz, University of Tübingen, Germany
Paul Crook, Microsoft, USA
Mary Ellen Foster, Heriot-Watt University, UK
Helen Hastie, Heriot-Watt University, UK
Jesse Hoey, University of Waterloo, Canada
Filip Jurcícek, Charles University in Prague, Czech Republic
Simon Keizer, Heriot-Watt University, UK
Kazunori Komatani, Nagoya University, Japan
George Konidaris, MIT CSAIL, USA
Honghai Liu, University of Portsmouth, UK
Ramon Lopez de Mantaras, Spanish Council for Scientific Research, Spain
Eduardo Morales, National Institute of Astrophysics, Optics and Electronics, Mexico
Plinio Moreno, Instituto Superior Técnico, Portugal
Olivier Pietquin, Supelec, France
Matthew Purver, Queen Mary University of London, UK
Antoine Raux, Honda Research Institute, USA
Alex Rudnicky, Carnegie Mellon University, USA
Hiroshi Shimodaira, University of Edinburgh, UK
Danijel Skocaj, University of Ljubljana, Slovenia
Blaise Thomson, University of Cambridge, UK
Zhuoran Wang, Heriot-Watt University, UK
Marco Wiering, University of Groningen, The Netherlands
Jason Williams, Microsoft Research, USA
Junichi Yamagishi, University of Edinburgh, UK

For all enquires, please mail: organizers@mlis-workshop.org