Wednesday, 18 July 2018

Call for Participation: 8th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics in Tokyo

Conference: September 16th – 20th, 2018
Early-registration period: September 2nd, 2018

Keynote Speakers

Prof. Oliver Brock (Technische Universität Berlin, Germany)
Title: Proposals for a Developmental AI

Prof. Kenji Doya (Okinawa Institute of Science and Technology, Japan)
Title: What can we learn from the brain for AI

Prof. Peter Marshall (Temple University, U.S.A.)
Title: Embodiment and Human Development

Mr. Masahiro Fujita (Sony, Japan)
Title: AIxRobotics in Sony

Information and Calls for Papers/Posters/Participation at Conference Workshops

All three workshops below will be  held Monday, September 17th, 2018

Understanding Developmental Disorders: From Computational Models to Assistive Technology
Organizers: Anja Kristina Philippsen*, Yukie Nagai

Aim and scope

The mechanisms of cognitive and developmental processes in humans are still far from being understood. It remains a mystery how our brain is capable of integrating high-dimensional sensory information from various sources in order to act and interact in a highly volatile environment. The amount of processing that our brain performs on an unconscious level becomes especially noticeable if the development of these mechanisms is atypical. Subjects with developmental disorders such as autism spectrum disorder (ASD) experience various difficulties in everyday life, particularly in social interactions. The causes are assumed to lie with atypical perception as well as differences in cognitive processing during the course of development.

In order to provide assistance for people with developmental disorders, it is crucial to understand more about the underlying mechanisms of cognitive and social development. In recent years, a number of novel approaches emerged for explaining differences in cognitive processes, for instance, in terms of Bayesian inference. By replicating autistic behavior in computational models or robots, or by studying the interaction patterns of children with ASD in interaction with a robot, possible mechanisms of cognitive development can be identified and systematically evaluated. The understanding we can gain from such experiments can help to overcome difficulties in communication between people with and without such disorders.

Another pathway for providing assistance for people with developmental disorders targets at developing assistive technology directed specifically toward ASD subjects, offering them assistance in understanding and participating in social interactions, or allowing them to train and explore interaction skills in therapy with a robot.

This workshop focuses on these two ways of how to assist people with developmental disorders, and discusses what we can learn from these studies about cognitive development in general. To connect and reflect these ideas, insights from developmental psychology, cognitive sciences, robotics and computational modeling are taken into account, as well as the perspective of people with ASD themselves (“Tojisha-Kenkyu”).

We invite the submission of 2-page paper abstracts which will be presented during the poster session.

Submission opens in mid-June 2018.

Active vision, Attention, and Learning
Organizers: Chen Yu*, David Crandall

Continual Unsupervised Sensorimotor Learning
Organizers: Nicolás Navarro-Guerrero*, Sao Mai Nguyen, Erhan Oztop, Junpei Zhong

Aim and Scope

As the algorithms for learning single tasks in restricted environments are improving, new challenges have gained relevance. They include multi-task learning, multimodal sensorimotor learning and lifelong adaptation to injury, growth and ageing.

In this workshop we will discuss the developmental processes involved in the emergence of representations of action and perception in humans and artificial agents in continual learning. These processes include action-perception cycle, active perception, continual sensory-motor learning, environmental-driven scaffolding, and intrinsic motivation.

The discussion will be strongly motivated by behavioural and neural data. We hope to provide a discussion friendly environment to connect with research with similar interest regardless of their area of expertise which could include robotics, computer science, psychology, neuroscience, etc. We would also like to devise a roadmap or strategies to develop mathematical and computational models to improve robot performance and/or to attempt to unveil the underlying mechanisms that lead to continual adaptation to changing environment or embodiment and continual learning in open-ended environments.

Short paper (max 4 pages)
Paper submission deadline: 29th July 2018

=== Committee ===

Tetsuya Ogata (Waseda University, Japan)

Angelo Cangelosi (Plymouth University, UK)

Tadahiro Taniguchi (Ritsumeikan University, Japan)

Emre Ugur (Bogazici University, Turkey)

Junko Kanero (Koç University, Turkey)

Erhan Oztop (Özyeğin University, Turkey)

Minoru Asada (Osaka University, Japan)

Giulio Sandini (Italian Institute of Technology, Italy)

Alessandra Sciutti (Italian Institute of Technology, Italy)

Philippe Gaussier (University of Cergy-Pontoise, France)

Hiroki Mori (Waseda University, Japan)

Alexandre Pitti (University of Cergy-Pontoise, France)

Umay Suanda (University of Connecticut, USA)

Shingo Shimoda (Riken, Brain Science Institute, Japan)

Tetsunari Inamura (NII, Japan)

Hiromi Mochiyama (Tsukuba University, Japan)

Takato Horii (The University of Electro-Communications, Japan)

Shingo Murata (Waseda University, Japan)

=== Contacts ===

Alex Pitti:
Hiroki Mori:
Umay Suanda:

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