Rob and Chris, (01)
Since both of you seem to approve of Selmer Bringsjord's paper,
that is a good starting point for resolving this debate: (02)
http://kryten.mm.rpi.edu/connectionist_logicist_clash.pdf (03)
As Selmer says in his one-sentence abstract, (04)
SB> A careful adjudication of the connectionist-logicist clash in AI
> and cognitive science seems to disclose that it is a mirage. (05)
The issue to be resolved is to analyze that mirage and show how the
heat of this debate is bending the light to create the mirage. (06)
CM>> You have yet to identify a single problem. Can you articulate one? (07)
RF> Knowledge soup. (08)
Thank you for referring to the term I used in my paper, (09)
http://www.jfsowa.com/pubs/challenge.pdf
The Challenge of Knowledge Soup (010)
But I used that term to characterize the immense complexity of what
people have in their heads, most of which is derived from the immense
complexity of the world, society, etc., as processed by the very large
human brains. The challenge is more than just a single problem. (011)
My recommended way of addressing the challenge is compatible with
Selmer B's recommendation of 'Ecumenical AI', which makes a judicious
selection and integration of elements from both sides of the clash. (012)
As a basis for integration, I have recommended Peirce's semiotics,
which provides a vocabulary that defuses the clash between symbolic
vs. subsymbolic approaches by a simple strategy: recognize that both
sides are talking about *signs* and that the first step is to analyze,
classify, and relate signs. For a brief summary of that analysis and
classification, see Section 2 of the following paper: (013)
http://www.jfsowa.com/pubs/pursuing.pdf
Pursuing the Goal of Language Understanding (014)
The remainder of that paper discusses many issues, and the slides that
accompany it may be easier to follow. In particular, see slides 26-37,
which include screen shots of an application to language processing
that uses a combination of both continuous math and symbolic methods: (015)
http://www.jfsowa.com/talks/pursuing.pdf
Slides that accompany the above paper (016)
RF> Wasn't a reconciliation of the connectionist and logicist
> paradigms the central theme of Simon Levy's presentation in
> particular, of the references I gave? (017)
Yes, he was trying to do something along the lines of processing
low-level (subsymbolic) signs to support logic (symbolic signs).
That is also compatible with Selmer's recommendation. But note
that he didn't reject logic. He proposed new methods to support
logic in a way that may be closer to what people do. (018)
RF> People commonly use vectors of contexts to represent word meaning. (019)
Just because some AI researchers use vectors to simulate some aspects
of human cognition does *not* imply that people process vectors in
their heads. That is just as much a non sequitur as assuming that
people have theorem provers in their heads. (020)
RF> I built a system to break natural language sentences into
> meaningful parts on this basis. (021)
That may be a useful mechanism to do one useful step in NLP, but
there are infinitely more continuous methods than digital methods. (022)
I would encourage you or anybody else who has a promising method
to develop it and demonstrate its potential. But finding the
best (or even a good) simulation in an uncountable infinity of
continuous methods is a nontrivial task. (023)
Good luck, (024)
John (025)
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