[Comp-neuro] [meetings] Call for Participation : Workshop on Continual Unsupervised Sensorimotor Learning - Tokyo - September 17th

Nguyen, Sao Mai nguyensmai at gmail.com
Fri Sep 14 16:42:58 CEST 2018

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

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

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
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
16:40 – 17:40 Discussion
17:40 – 18:00 Conclusions and farewell



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

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
- Multisensory robot learning
- Multimodal sensorimotor learning
- Affordance learning
- Prediction learning


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 at gmail.com
Researcher in Cognitive Developmental Robotics
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