Davidsson: Toward a General Solution to the Symbol Gorunding Problem
http://www.cogsci.soton.ac.uk/~harnad/Temp/CM302/davidsson.pdf
> DAVIDSON:
> A possible solution to this problem would be to attempt to describe the
> meaning of the symbols in a more powerful language. However, this would
> only lead to another set of symbols, ones which would otherwise nee to be
> interpreted, and in the end to an infinite regression.
I fully agree!
Has anyone any ideas about approaching this the opposite way? Give
grounding to symbols using a lower level language. By doing this will the
regression lead to insugnificantly small and pointless symbols so as not
to matter?
OR...
Ground symbols in relation to eachother, although this will lead to an
infinite loop of referals in the search for a grounding.
> DAVIDSON:
> Concerning Harnads approach, one can remark that, although it seems clear
> that a pure symbolic system does not suffice .....
> .....regarding connectionist networks alone as being capable of serving
> this function appears too limited.
Connectionist networks (Neural Nets, back propogation) can't learn from
single pieces of training data.
> DAVIDSON:
> One such restriction is that the algorithm must be incremental. Since
> the robot cannot control the environment, it will prbably not encounter
> all instances of a catagory at one point in time.
Harnad, Please respond.
> DAVIDSON:
> .....the first is that designers tend to program their own grounding
> based on thier own experience.....
This non-explicit approach will restrict the potential of any system
designed in this way.
The argument of vision being neccesary and thusly symbolic representations
will not be needed I find hard to understand. If thier are no symbols
then what does the system malipulate in order to perform any function.
As DAVIDSON states, if this is the case the symbol grounding problem is
irrelavent and he goes on the say that no matter what the system uses it
still MUST have some sort of concepts.
DAVIDSON sets out to find a general solution for the symbols grounding
problem. He suggests the type of learning that would be needed
(incremental) and that it have to learn for example and from experience.
This has not yet been achieved, as DAVIDSON states but when it is I
believe that DAVIDSON's argument for a visual (or at least multi sensual)
learning system will be the most affective approach that has been
described along this course. HARNAD's solution although workable does
have the problem with the potential lack of back propogation and does not
include much supervised learning which I believe is neccersary to increase
the rate of learning in the early stages as an unsupervised system may
take some years to learn and will still not interact with humans without
some example of OUR grounding rules.
_______________________________________________________________________________
Pentland, Gary
GP397@ECS.SOTON.AC.UK
_______________________________________________________________________________
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