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

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

Philipp Zech
*Apologies for cross posting*


Special Issue on "Computational Models of Affordance for Robotics" in
Adaptive Behavior

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=aPwg4Cq0Srzbl5psIHOxmAjpSKMs3wOXsqadOM7Iz6o&s=93j1acPRwQHBOhwGZsMUtN0-6ehqoUXgoXY4bVxnMkE&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
[hidden email]

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

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