[robotics-worldwide] [journals] CfP: Special Issue on "Computational Models of Affordance for Robotics" in Adaptive Behavior

Philipp Zech philipp.zech at uibk.ac.at
Tue Jul 3 23:54:18 PDT 2018

*Apologies for cross posting*


Special Issue on "Computational Models of Affordance for Robotics"

Gibson's theory of affordance, in its adherence to bottom-up direct 
perception, is antithetical to the top-down inferential models often 
proposed by modern robotics research purporting to tackle it. Such 
research assumes internal representation to be sacrosanct, but given 
current developments, to what extent can this assumption now be 
reexamined? The recently proposed sensorimotor contingency theory 
furthers the theoretical argument that internal representation is 
unnecessary, and its proof-of-concept application in robotics as well as 
the subsequent explosion in deep learning methodology sheds new light on 
the possibility of equipping robots with the capacity for directly 
perceiving their environments by exploiting correlated changes in their 
sensory inputs triggered by executing specific motor programs. This
reexamination of direct perception is only one of several issues 
warranting scrutiny in current robotic affordance research.

The aim of this special issue is to highlight the relevance of Gibson's 
notion of affordance for developmental and cognitive robotics. The issue 
is focused on contributions from the current panorama of robotics with 
an emphasis on theories from the ecological, cognitive, developmental 
and sensorimotor accounts.

We welcome submissions of all types (original research articles, 
reviews, short communications, and opinions) related to affordances and 
robotics, including but not limited to the following topics:

- Affordance learning
- Multimodal affordance learning
- Affordance perception and vision for affordances
- Perceptual learning and development
- Babbling and exploration
- Language and affordances
- Learning from observation and mirroring
- Self-organization of knowledge
- Deep learning of affordances
- Bayesian learning of affordances
- Concept learning
- Symbol emergence
- Symbol grounding
- Sensorimotor contingency theory
- Behavior affording behavior
- Actions and functions in object perception
- Brain-body-environment systems
- Agent-environment systems
- Selective attention
- Self-supervised learning
- Sensing physical properties
- Ecologically intuitive physics

This special issue is being released in conjunction with the 1st 
International workshop on "Computational Models of Affordance in 
Robotics" (https://urldefense.proofpoint.com/v2/url?u=https-3A__afford.gitlab.io_rss-2Dworkshop_&d=DwIDaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=Sk7PwkiO2BmGzPkPezvnwbiqPVXmHI8NdPdGTmI5zhc&s=5Ks2p-ey_UAOeNYwlbKIGnbCWKyvNL8-LRJyyhCCKFs&e=) to be held at the 
2018 Robotics: Science and Systems conference in Pittsburgh, PA, USA. We 
encourage authors to submit early versions of their planned 
contributions to this workshop.

Submission of papers:          October 1, 2018
Reviewer's feedback due:      November 30, 2018
Revised submission due:      January 31, 2019
Publication date:                     Summer 2019

Philipp Zech, University of Innsbruck, Austria
philipp.zech at uibk.ac.at

Barry Ridge, Jožef Stefan Institute, Slovenia
Emre Ugur, Bogazici University, Turkey

Intelligent and Interactive Systemhttps://iis.uibk.ac.at/
Department of Computer Science, University of Innsbruck, Austria

More information about the robotics-worldwide mailing list