Proceedings of the 2nd Conference on Artificial General Intelligence (2009)

A formal framework for the symbol grounding problem

Authors
Benjamin Johnston, Mary-Anne Williams
Corresponding Author
Benjamin Johnston
Available Online June 2009.
DOI
10.2991/agi.2009.12How to use a DOI?
Abstract

A great deal of contention can be found within the published literature on grounding and the symbol grounding problem, much of it motivated by appeals to intuition and unfalsifiable claims. We seek to define a formal framework of representa- tion grounding that is independent of any particular opinion, but that promotes classification and comparison. To this end, we identify a set of fundamental concepts and then formalize a hierarchy of six representational system classes that corre- spond to different perspectives on the representational require- ments for intelligence, describing a spectrum of systems built on representations that range from symbolic through iconic to distributed and unconstrained. This framework offers utility not only in enriching our understanding of symbol grounding and the literature, but also in exposing crucial assumptions to be explored by the research community.

Copyright
© 2009, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd Conference on Artificial General Intelligence (2009)
Series
Advances in Intelligent Systems Research
Publication Date
June 2009
ISBN
978-90-78677-24-6
ISSN
1951-6851
DOI
10.2991/agi.2009.12How to use a DOI?
Copyright
© 2009, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Benjamin Johnston
AU  - Mary-Anne Williams
PY  - 2009/06
DA  - 2009/06
TI  - A formal framework for the symbol grounding problem
BT  - Proceedings of the 2nd Conference on Artificial General Intelligence (2009)
PB  - Atlantis Press
SP  - 50
EP  - 55
SN  - 1951-6851
UR  - https://doi.org/10.2991/agi.2009.12
DO  - 10.2991/agi.2009.12
ID  - Johnston2009/06
ER  -