Symbol grounding is an empirical problem: Neural nets are just a candidate component

Abstract

"Symbol Grounding" is beginning to mean too many things to too many people. My own construal has always been simple: Cognition cannot be just computation, because computation is just the systematically interpretable manipulation of meaningless symbols, whereas the meanings of my thoughts don't depend on their interpretability or interpretation by someone else. On pain of infinite regress, then, symbol meanings must be grounded in something other than just their interpretability if they are to be candidates for what is going on in our heads. Neural nets may be one way to ground the names of concrete objects and events in the capacity to categorize them (by learning the invariants in their sensorimotor projections). These grounded elementary symbols could then be combined into symbol strings expressing propositions about more abstract categories. Grounding does not equal meaning, however, and does not solve any philosophical problems

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 91,349

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

  • Only published works are available at libraries.

Analytics

Added to PP
2009-01-28

Downloads
136 (#132,152)

6 months
6 (#522,885)

Historical graph of downloads
How can I increase my downloads?

Author's Profile

Stevan Harnad
McGill University

Citations of this work

Embodied cognition and linguistic comprehension.Daniel A. Weiskopf - 2010 - Studies in History and Philosophy of Science Part A 41 (3):294-304.
Why and how we are not zombies.Stevan Harnad - 1994 - Journal of Consciousness Studies 1 (2):164-67.

Add more citations

References found in this work

No references found.

Add more references