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AIList Digest Volume 5 Issue 190
AIList Digest Wednesday, 29 Jul 1987 Volume 5 : Issue 190
Today's Topics:
Queries - AI/Graphics & Examples of KEE Frames &
Problem Recognition in Prolog Databases &
NLP Front Ends to INGRES,
Policy - Virtual Sublists,
Philosophy - Natural Kinds
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Date: Mon, 27 Jul 87 14:03:36 BST
From: mcvax!ux.cs.man.ac.uk!arnold@seismo.CSS.GOV
Reply-to: thoward@uk.ac.man.cs.cgu
Subject: AI/Graphics: help wanted
I am currently investigating what work has been done on connecting/
integrating AI methods and computer graphics. I would be very grateful
if anyone can send me any references, or bibliographies (or comments!)
etc in this area. If there's enough interest, I will summarise responses.
Please mail to me directly, *not* to the source of this posting, as it's
not my own account. Thanks...
Toby Howard Janet: thoward@uk.ac.man.cs.cgu
University of Manchester ARPA: thoward%cgu.cs.man.ac.uk@cs.ucl.ac.uk
Computer Graphics Unit Phone: +44 61 273 7121 x5429/5406
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Date: 28 Jul 87 04:46:37 GMT
From: munnari!uqcspe.OZ!twine@uunet.UU.NET (Steven Twine)
Subject: Examples of KEE frames Requested
I am currently revising a semantic analysis of KEE's frame language.
By semantic analysis, I mean trying to answer the question
What facts does X encode about the current Universe of Discourse
where X is each of the syntactic ingredients in a KEE knowledge base
(units, slots, links etc).
This is not as simple as it seems, because a given KEE construct can
represent many different things (as Brachman showed for IsA links).
Anyway, in revising this paper, I would like to add many more examples
of KEE structures that have been used in practice, for the
purpose of analysing the facts that they encode. I am particularly
interested in any ambiguous or otherwise tricky examples that I can
test my interpretations out on. I would appreciate any examples of
KEE units etc that people could send me for this purpose (examples in
other frame languages may also be useful, but KEE is preferred)
All senders will get a lovely acknowledgement at the end of the paper
(what an incentive!) as well as my heartfelt gratitude.
Thanks in advance, folks!
=========================================================================
Steven Twine, ARPA: twine%uqcspe.oz@seismo.css.gov
Department of Computer Science, ACSnet: twine@uqcspe.oz
University of Queensland, UUCP: seismo!munnari!uqcspe.oz!twine
St Lucia, 4067. CSNET: twine@uqcspe.oz
AUSTRALIA. JANET: uqcspe.oz!twine@ukc
------------------------------
Date: 26 Jul 87 20:37:16 GMT
From: dartvax!balu.UUCP@seismo.css.gov (Balu Raman)
Subject: Problem recognition in Prolog database
I am working on recognizing problem instances in Prolog database. The problems
can be typical Graph-color, Linear Programming Problem, Critical Path Problems
etc.etc. Does anybody in the netland have references, pointers ,prolog programs
to do what I am trying to do.
thanks in advance.
Balu Raman.
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Date: Mon, 27 Jul 87 08:37:24 PDT
From: vor!cris%esosun.UUCP@sdcsvax.ucsd.edu (Cris Kobryn)
Subject: NLP Front-Ends to INGRES
I am interested in developing an NLP front-end to INGRES. Lest I
reinvent: Is there any "stock" software which already does this?
(INTELLECT does not *currently* accommodate INGRES; I've heard "DataTalker"
mentioned as a possibility, but have no details--capabilities, company name,
phone#, etc.)
Re building an NLP front-end: Prolog's DCG's (Definite Clause Grammars)
seem to provide an attractive tool to construct an NLP front-end. I would
appreciate feedback re their effectiveness, and pointers to work done or
being done relevant to this interest.
I will be glad to summarize and post if the response merits it.
-- Cris Kobryn
+----------------------------------------------------------------------------+
| Cris Kobryn UUCP: {sdcsvax|seismo}!esosun!cris |
| Geophysics Division, MS/22 ARPA: esosun!cris@seismo.css.gov |
| SAIC SOUND: (619)458-2697 |
| 10210 Campus Point Drive |
| San Diego, CA 92121 |
+----------------------------------------------------------------------------+
------------------------------
Date: 27 Jul 87 14:28 PDT
From: Ghenis.pasa@Xerox.COM
Subject: PROPOSAL: We need "virtual sublists"
The recent meta-discussion on what to include in the Digest was rather
similar to the one about whether to include the AI Expert code listings.
At that time I made a proposal that may have drowned in the noise. I
still think it would solve the filtering problem so here it goes:
PROBLEM:
You can't tell what is inside the digest until you start reading it. The
title is non-descriptive. How does an AIList reader filter unwanted
topics?
If a reader has an unsophisticated mail reading channel, there is an
irritating time cost to opening an unwanted 20,000 character message.
This is even worse for folks who read their mail through a modem
connection.
Proposing the creation of a new list for each topic that generates a
large mail volume is not only unrealistic but also unnecessary.
SOLUTION:
The moderator is already thoughtful enough to segregate topics so that
each digest is fairly homogeneous. Now if only the "Subject:" line could
read
AIList V5 #183 - Symbol Grounding
instead of
AIList Digest V5 #183
then it would be easy to filter topics even with the crudest of mail
programs, and our personal archives would also be much more descriptive
at the table-of-contents level.
I believe that this scheme would address the objections of folks who
voted against continuing to distribute symbol grounding messages or
source code listings.
MODERATOR: Would this be a difficult change to implement?
FELLOW READERS: Is this proposal missing the point? Is there anything
else we could do to better prepare for the next large discussion? Should
we move this discussion to the META-META-DISCUSSIONS list? :-)
Pablo Ghenis
Xerox Artificial Intelligence Systems
Educational Services
[This has been suggested several times, by several people, so
I might as well give it a try. I am reminded, though, of a
parody of Reader's Digest that condensed an entire Hemmingway
novel to the word "Bang!". A good many digests will have to
be tagged as "Msc.", including this one.
I really don't see the advantage in the longer subject line,
but perhaps that is because my mailer clips the subject at about
40 characters. The cost of examining the full Topics section
is only about one page of data. (Are there really mailers out
there that let you read the subject line without the cost of
"pulling in" the entire digest?)
What is really needed here is an intelligent mail-reading system.
I'm sure that special digest-reading commands could -- but
probably won't -- be added to any of our mailers. Even better
would be an intelligent Information Lens system. Won't someone
take this on as an AI project? -- KIL]
------------------------------
Date: 27 Jul 87 09:45:19 edt
From: Walter Hamscher <hamscher@ht.ai.mit.edu>
Subject: Natural Kinds (Re: AIList Digest V5 #186)
Your functional description of "chair" does capture more of "what's
essential to chairs" than the structural description could. Some
quibbles, however. First, it includes couches since it doesn't say
that it's for exactly one person. Second, it doesn't seem to include
"Balenz" chairs, those kind in which the person rests on his/her
shins, since the "support for one's back" is rather indirect -- what
they do is to make it easier to balance the spine by tilting the
pelvis forward. Third, some people might say that Balenz chairs
aren't chairs at all, but stools, because the back support is indirect
-- the point being that the functional description might have to take
into account who's saying what about chairs to whom. Probably, other
Ailist readers will come up with more borderline cases, which brings
me to the speculation that functional descriptions may end up with as
many exceptions as structural descriptions do.
------------------------------
Date: Mon, 27 Jul 1987 11:16 EDT
From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU
Subject: Natural Kinds (Re: AIList Digest V5 #186)
I agree:
1. Yes, I think we'd all agree that a chair is for 1 person to sit on.
2. The boundary is fuzzy, indeed, and some people might not
consider a Balenz chair to be a chair.
3. Yes, indeed, the "functional description" does indeed depend on
whose "intention" is ivolved, and upon who is saying what to whom.
My point is not that such terms can be defined in foolproof, clear-cut
ways. There are really two sorts of points.
1. You can get much further in making good definitions by squeezing
in from both structural and function directions - and surely others as well.
2. In Society of Mind, section 30.1 I discuss how meanings must depend on
speakers, etc.
As Ken Laws remarked, we should not be too hasty to thank philosophers
for concept of "natural kind". McCarthy make useful remarks about
penguins, which form a clear-cut cluster because of the speciation
mechanism of sexual reproduction. The class is un-fuzzy even though,
as McCarthy notes, penguins have properties that scientists have not
yet discovered.
But then, I think, McCarthy defeats this clarity by proceeding to
discuss how children learn about chairs - and tries to subsume this,
too, into natural kinds. He describes what seems clearly to be not
"natural" aspects of chairs, but the clustering and debugging
processes a child might use.
My conclusion - and, I'd bet, Ken Laws would agree - is that the
concept of "natural kind" has an illusory generality. It seems to me
that, rather than good philosophy, it is merely low-grade science
contaminated by naive, traditional common sense concepts. The
clusters that have good boundaries, in the world, usually have them
for good - but highly varied reasons. Animals form good clusters
because of Darwinian speciation of various sorts. Certain metals,
like Gold, have "natural" boundaries because of the Pauli exclusion
principle which causes things like periodic tables of elements.
Philosophers like to speak about gold - but their arguments won't work
so well for Steel, whose boundary is fuzzy because there are so many
ways to strengthen iron. All in all, the clusters we perceive that
have sharp boundaries are quite important, pragmatically, but exist
for such a disorderly congeries of reasons that I consider the
philosophical discussion of them to be virtually useless in this
sense: the class of clusters with "suitable sharp boundaries" to
desaerve the title "natural kinds" is itself too fuzzy a concept to
help us clarify the nature of how we think about things.
------------------------------
Date: Mon, 27 Jul 87 09:57:26 MDT
From: shebs@cs.utah.edu (Stanley Shebs)
Reply-to: cs.utah.edu!shebs@cs.utah.edu (Stanley Shebs)
Subject: Re: Natural Kinds (Re: AIList Digest V5 #186)
In article <MINSKY.12320404487.BABYL@MIT-OZ> MINSKY@OZ.AI.MIT.EDU writes:
>About natural kinds. In "The Society of Mind", pp123-129, I propose a
>way to deal with Wittgenstein's problem of defining terms like "game"-
>or "chair". The basic idea was to probe further into what
>Wittgenstein was trying to do when he talked about "family
>resemblances" and tried to describe a game in terms of properties, the
>way one might treat members of a human family: build, features, colour
>of eyes, gait, temperament, etc.
>[... details of Wittgenstein vs Minsky :-) ...]
>I would appreciate comments, because I think this may be an important
>theory, and no one seems to have noticed it. [...]
I recently finished reading "Society of Mind", and quite enjoyed it.
There are a lot of interesting ideas. There are also many that are
familiar to people in the field, but with new syntheses that make the
ideas much more plausible than in the past. I had been getting cynical
about AI, but after reading this, I wanted to go and hack out programs
to test the hypotheses about action, and memory, and language. But there's
a serious problem; how *can* these hypotheses be tested? The society of
mind follows human thinking so closely that any implementation is going
to be a model of human minds rather than minds in general, and will probably
be handicapped by being too small and simple to be recognizably human-like
in its behavior. Tracing a mind society's behavior will generate lots
of data but little insight. So my ardor has been replaced by odd moments
speculating on tricky but believable tests, and a greater appreciation for
people interested in a more formal approach to minds.
Getting down to specifics, the theory about recognition of objects by either
structure or functions was one of the parts I really liked. A robot should
be able to sit on a desk without getting neurotic, or to sit carefully on
a chair that's missing one leg...
stan shebs
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End of AIList Digest
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