Call for Participation

Workshop on Continual Unsupervised Sensorimotor Learning at IEEE ICDL-Epirob 2018 - Tokyo - September 17th

Website : http://conferences.au.dk/icdl-epirob-2018-workshop/
============================================================

Updated list of Invited Speakers

- Jochen Triesch, Frankfurt Institute of Advanced Studies, Germany

Title: Active Efficient Coding

- David Ha, Google Brain

Title: Generative World Models

- Kathryn Kasmarik, University of New South Wales, Australian Defence Force Academy

(UNSW Canberra), Australia
Title: Computational Motivation for Learning, Optimisation and Decision Making

Schedule

09:50 – 10:10	Welcome and introduction
10:10 – 10:50	Invited talk: David Ha Title: Generative World Models
10:50 – 11:10	Coffee break
Inference and Representations
11:10 – 11:30	Where do I move my sensors? Emergence of an internal representation from the sensorimotor flow Valentin Marcel, Sylvain Argentieri and Bruno Gas
11:30 – 11:50	Active inference in continual learning Pablo Lanillos
Sensorimotor Learning
11:50 – 12:10	Towards Biological Plausibility of Sensorimotor Learning Models: a Short Review Silvia Pagliarini, Arthur Leblois, and Xavier Hinaut
12:10 – 12:30	A Computational Model For Action Prediction Development Serkan Bugur, Yukie Nagai, Erhan Oztop, and Emre Ugur
Application/Tools
12:30 – 12:50	Flatland: a Lightweight First-Person 2-D Environment for Reinforcement Learning Hugo Caselles-Dupré, Louis Annabi, Oksana Hagen, Michael Garcia-Ortiz, and David Filliat
12:50 – 14:10	Lunch break
14:10 – 14:50	Invited talk. Jochen Triesch Title: Active Efficient Coding
Intrinsic Motivation and alike
14:50 – 15:10	Learning Sequences of Policies by using an Intrinsically Motivated Learner and a Task Hierarchy Nicolas Duminy, Alexandre Manoury, Sao Mai Nguyen, Cédric Buche, and Dominique Duhaut
15:10 – 15:30	Emergent emotion as a regulatory mechanism for a cognitive task implemented on the iCub robot Murat Kirtay, Lorenzo Vannucci, Egidio Falotico, Cecilia Laschi, and Erhan Oztop
Application/Tools
15:30 – 15:50	Towards Life Long Learning: Multimodal Learning of MNIST Handwritten Digits Eli Sheppard, Hagen Lehmann, G. Rajendran, Peter E. McKenna, Oliver Lemon, and Katrin S. Lohan
15:50 – 16:10	Coffee break
16:10 – 16:40	Invited talk: Kathryn Kasmarik Title: Computational Motivation for Learning, Optimisation and Decision Making
16:40 – 17:40	Discussion
17:40 – 18:00	Conclusions and farewell

============================================================

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 in open worlds 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.

The primary list of topics covers the following (but not limited to):
- Emergence of representations via continual interaction
- Continual sensory-motor learning
- Action-perception cycle
- Active perception
- Environmental-driven scaffolding
- Intrinsic motivation
- Neural substrates, neural circuits and neural plasticity
- Human and animal behaviour experiments and models
- Reinforcement learning and deep reinforcement learning for life-long learning
- Multisensory robot learning
- Multimodal sensorimotor learning
- Affordance learning
- Prediction learning

Organizers:

Nicolás Navarro-Guerrero, Aarhus University, Aarhus, Denmark

Sao Mai Nguyen, IMT Atlantique, France

Erhan Öztop, Özyeğin University, Turkey

Junpei Zhong, National Institute of Advanced Industrial Science and Technology (AIST), Japan

============================================================

Nguyen Sao Mai
nguyensmai@gmail.com
Researcher in Cognitive Developmental Robotics
http://nguyensmai.free.fr