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AIList Digest Volume 4 Issue 030
AIList Digest Monday, 17 Feb 1986 Volume 4 : Issue 30
Today's Topics:
Query - Ambiguous Sentences,
Cognitive Psychology - Definition & Novice-Expert Differences,
Theory - Dreyfus' Technology Review Article
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Date: Fri 14 Feb 86 14:29:21-PST
From: FIRSCHEIN@SRI-AI.ARPA
Subject: Ambiguous sentences.
I wonder whether AILIST readers have a favorite short sentence for
illustrating multiple ambiguity, say greater than 5 meanings?
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Date: Sat, 15 Feb 86 21:38:39 EST
From: bzs%bostonu.csnet@CSNET-RELAY.ARPA
Subject: Re: Sparklers from the Tech Review
>From: larry@Jpl-VLSI.ARPA
>COGNITIVE PSYCHOLOGY (a more restricted area than Cognitive Science) attempts
>to understand biologically based thinking using behavioral and psychiatric
>concepts and methods. This includes the effects emotional and social forces
>exert on cognition. This group is increasingly borrowing from the following
>groups.
Just curious, but as an undergraduate studying such things at Cornell
in the early 70's I remember being lectured over and over again about
'Cognitive Psychology' which at that point in time seemed to be a
school derived largely from Festinger's works in Cognitive Dissonance
et al (and Brehm and others.) It was generally posed as being
orthogonal to behaviorism (Skinnerianism.) Is this the same 'cognitive
psychology' I suffered through? Or has the term changed? What do they
call the old stuff, or are we allowed to speak of it anymore (oops)? I
suppose this definition *might* be referring to the same thing, but I
don't see how.
-Barry Shein, Boston University
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Date: 14 Feb 86 14:38:36 EST (Fri)
From: Robert Rist <rist@YALE.ARPA>
Subject: novice-expert differences
You can trace back the articles you need if you look at
Snow, R. E., Federico, P. & Montague, W. E. (Eds.). (1980) Aptitude,
learning and instruction, Volume 2. This has articles by VanLehn and
Brown, Stevens and Collins, Anderson and Norman.
Lesgold, A. M. (1984). Acquiring expertise. In Anderson and Kosslyn
(Eds.), Tutorials in learning and memory. Pointers to lots of
different research domains.
Chi, M. T. H., Glaser, R. & Rees, E. (1982). Expertise in problem
solving. In Sternberg, R. J. (Ed.), Advances in the psychology of
human intelligence. This is one of the best summary articles I have
seen.
Anderson, J. R. (Ed.) (1981). Cognitive skills and their acquisition.
A mixed bag, but it contains some real classics.
Gentner, D. & Stevens, A. L. (1983). Mental models. The stuff on
multiple models and debugging is very interesting.
If you're interested in learning, you could also look at
Anzai, Y. (1984). Cognitive control of real-time event-driven systems.
Cognitive Science, 8, 221-254.
Anzai, Y. & Simon, H. A. (1979). The theory of learning by doing.
Psych. Review, Vol 86, 124-140.
Anderson, R. J. (1985). Cognitive psychology and its implications.
This has a chapter on expertise development that gives an overview
plus list of references.
Have fun, Rob Rist
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Date: Thu, 13 Feb 86 09:44:18 est
From: rjk@mitre-bedford.ARPA (Ruben)
Subject: Response to "Thompson@umass-cs.csnet" re: "Expertize"
In lieu of replying to the apparently incorrect address
"Thompson@umass-cs.csnet", I send my tidbit to the AILIST.
>From an abstract but empirically motivated view of the relationship
between expertise and category formation (a criterion useful for
discriminating relatively novice from expert behavior), I suggest
Eleanor Rosch's (U. of C. at Berkeley) work on prototypes.
A particularly good SUMMA is her article "Human Categorization,"
of which I read in draft form but which SHOULD (?) have been
published in ADVANCES IN CROSS-CULTURAL PSYCHOLOGY (Vol. 1),
M. Warren (ed.), Academy Press, London, circa 1976. I think
that her approach to categorization raises some intelligent and
persuable questions about the role of expertize in categorization:
this article is worth reading, even if it only touches on this question.
Rosch planned to do further research to follow up her questions viz.
expertize, but I have not yet seen it. (Let me know if you follow
this up.)
Ruben J. Kleiman rjk@MITRE-BEDFORD
[The address Thompson%UMASS-CS.CSNet@CSNet-Relay should work
(regardless of capitalization). The gateway requires that all
CSNet mail from the Arpanet be addressed to @CSNet-Relay, and that
all other @-signs be changed to %-signs. The .CSNet prior to the
@CSNet-Relay is sometimes optional. -- KIL]
------------------------------
Date: 8 Feb 86 00:35:57 GMT
From: decwrl!glacier!kestrel!ladkin@ucbvax.berkeley.edu
Subject: Re: Technology Review article
In article <15030@rochester.UUCP>, lab@rochester.UUCP (Lab Manager) writes:
> "In 3000 years, Philosophy has still not lived up to its promises and
> there's no reason to think it ever will."
An interesting comment. Whenever a problem is solved in Philosophy,
it spawns a whole new field of specialists, and is no longer called
Philosophy. Witness Physics, which used to be called Natural
Philosophy. When Newton took over, it gradually became a new
subject. Witness our own subject, which arose out of the
attempts of Frege to provide a formal foundation for mathematical
reasoning, via Russell, Church, Curry, Kleene, Turing and
von Neumann. Much work in natural language understanding arises
from the work of Montague, and more recently speech act theory
is being used, from Grice, Searle and Vanderveken.
The list goes on, and so do I. Would that AI bear such glorious
fruit. I think it might.
Peter Ladkin
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Date: 9 Feb 86 16:05:00 GMT
From: pur-ee!uiucdcs!uiucuxc!bantz@ucbvax.berkeley.edu
Subject: Re: Technology Review article
Dreyfus's book "What Computers Can't Do" was a pretty sorry affair, insofar
as it purported to have a positive argument about intrinsic limits of
computers. However uncomfortable it makes the AI community feel, though,
the journalistic baiting with extensive quotations from the AI community
itself, ought to have demonstrated the virtues of a bit more humility than
is often shown. [I'm refering to his gleeful quotation of predictions that,
by 1970 or so a computer would be world chess champion, that fully literate
translations of natural languages would be routine...]
The responses here, so far, seem to be guilty of what Dreyfus is accused of:
failing to engage the opponent seriously, and relying on personal expressions
of distaste or ridicule. Specifically, Dreyfus does reject the typology of
learning in AI, on the not implausible grounds that it is self-serving, and
not obviously correct (or uniquely correct).
[Please! I am *not* a fan of Dreyfus, and do not endorse most of his claims.]
------------------------------
Date: Sun 16 Feb 86 22:33:41-PST
From: Ken Laws <Laws@SRI-AI.ARPA>
Reply-to: AIList-Request@SRI-AI.ARPA
Subject: In Support of the Dreyfi
I have now had a chance to read the Technology Review article (thanks to
a copy from Oscar Firschein). If it is a fair sample of Hubert and
Stuart Dreyfus' forthcoming book, Mind Over Machines, the book should
be required reading. Not that I necessarily agree with their
positions -- I see their points as problems to be solved rather than
proofs of futility -- but they have now solidified their stronger
arguments and (I presume) shed many of their weaker ones. I recently
read the introduction to the second edition of Hubert's What Computers
Can't Do and found myself disagreeing with about one item per page.
(To be fair, they or anyone else would find similar disagreement with
my [fuzzy] ideas if I had the ability and temerity to expose them in
writing.) I did not experience anywhere near the same density of
objections to this new article, Why Computers May Never Think Like People.
I am optimistic that we will be able to build "digital" intelligences
(with perhaps a few analog circuits thrown in as necessary), but I
cannot support my optimisim as well as they support their pessimism.
They are right that the AI "paradigms" of the past have proven weak
and inextensible, and that those of the present are also likely to
fail. (Five years hence, will not each researcher's proposals start
with "Previous work in this field has had limited success due to ...,
but our new approach will ...?) They are wrong to assume that the
logic-based symbol-processing paradigm is the only card AI holds.
(Sorry, guys, but I'm not a logic lover. Explicit definitions and
rules for commonsense reasoning are a useful exercise, but flexible --
and sometimes errorful -- intelligence will ultimately depend on a
patchwork of heuristics and analogies.) Many of the "feature vs
aspect" problems raised by the brothers are being faced by those of
us researching perception. Our results are sparse to date, but that
is no proof that pattern recognition and concept formation are
inherently human capabilities. Hubert and Stuart, as the loyal
opposition to past naivete, may help us to face and overcome the
true difficulties in real-world intelligence -- if they don't get
our funding killed first.
-- Ken Laws
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End of AIList Digest
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