Call for contributions

Deadline: 21th August 2018 (extended)> submit

We invite participants to submit extended abstracts, short papers (max 4 pages) or 5 minutes videos of relevant work. Publications to be presented at the main conference are also welcome. The accepted contributions will be posted on the workshop website but they will not appear in the official IEEE proceedings. The reviewing is single blind and will be edited by the workshop organizers. The call in pdf can be downloaded here.

Please submit your abstract through easychair here before 21th August 2018 (extended). Any questions please send an email to selfception.workshop@gmail.com.

The template for the contributions is IEEE RAS workshop (Latex). The following categories are welcome:

• Extended abstract
• Short paper (max 4 pages)
• Video contribution (max 5'). Submit a pdf explaining the video and embed the link on the text

Accepted contributions will have the opportunity to present their work/ideas to the audience in a poster highlights slot. Up to 4 selective submissions will give a 20 min talk at the workshop. Please indicate in your email if you want to present as a poster/video or if you want to apply for the oral presentation slot.

Furthermore, a selective number of papers from the poster sessions will be invited to submit their novel work to the special issue we are proposing for journal to be defined. This special issue will cover the main topics of interest of this workshop.

Important Dates

Paper submission deadline: Extended 21th August 2018
Notification of acceptance:   1st September 2018
Camera ready version and slides (2-3 slides pdf or 5' video): 24th September 2018

Workshop day: 1st October 2018 

Topics of interest include, but are not limited to: 

• Body-model learning 
  • Self-exploration
  • Self-calibration
  • Self-modelling
• Self/other distinction
• Interactive perception
• Peripersonal space learning and protective safety zones
• Sensorimotor, intermodal and cross-modal patterns learning algorithms
• Embodied active perception, learning and interaction
  • Active inference and predictive processing in robots
  • Embodied causality
  • Interaction using body predictors
• Computational models of the self
  • Agency
  • Body-ownership
• Self-aware robots