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AIList Digest Volume 7 Issue 033
AIList Digest Wednesday, 15 Jun 1988 Volume 7 : Issue 33
Today's Topics:
Philosophy:
Who else isn't a science?
scope of ailist
Me, Karl, Stephen, Gilbert
Definition of Information
representation languages
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Date: 13 Jun 88 13:07:50 GMT
From: marsh@mitre-bedford.arpa (Ralph J. Marshall)
Subject: Re: Who else isn't a science?
In article <10785@agate.BERKELEY.EDU> weemba@garnet.berkeley.edu writes:
>
>Indeed, many modern dictionaries now give an extra meaning to the word
>"intelligent", thanks, partly due to AI's decades of abuse of the term:
>it means "able to peform some of the functions of a computer".
>
>Ain't it wonderful? AI succeeded by changing the meaning of the word.
>
>ucbvax!garnet!weemba Matthew P Wiener/Brahms Gang/Berkeley CA 94720
I don't know what dictionary you are smoking, but _MY_ dictionary has the
following perfectly reasonable definition of intelligence:
"The ability to learn or understand or to deal with new or
trying situations." (Webster's New 9th Collegiate Dictionary)
I'm not at all sure that this is really the focus of current AI work,
but I am reasonably convinced that it is a long-term goal that is worth
pursuing.
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Date: 14 Jun 88 07:25:00 EDT
From: "CUGINI, JOHN" <cugini@icst-ecf.arpa>
Reply-to: "CUGINI, JOHN" <cugini@icst-ecf.arpa>
Subject: scope of ailist
As a somewhat belated response to the complaints about endless
philosophizing, I offer the following quote from H.G. Wells, "The
Future in America", written in 1906, after Wells had toured the
states. He was writing specifically about Washington, providing some
additional poignancy for those of us who work in the DC area, but
perhaps it has wider pertinence:
It is perhaps near the truth to say that this dearth of any
general and comprehensive intellectual activity is due to
intellectual specialization. The four thousand scientific
men in Washington are all too energetically busy with
ethnographic details, electrical computations or herbaria,
to talk about common and universal things. They ought not to
be so busy, and a science so specialized sinks halfway down
the scale of sciences. Science is one of those things that
cannot hustle; if it does it loses its connexions. In
Washington some men, I gathered, hustle, others play bridge,
and general questions are left a little comtemptuously, as
being of the nature of "gas," to the newspapers and
magazines. Philosophy, which correlates the sciences and
keeps them subservient to the universals of life, has no
seat there. My anticipated synthesis of ten thousand minds
refused, under examination, to synthesize at all; it
remained disintegrated, a mob, individually active and
collectively futile, of specialists and politicians.
John Cugini <Cugini@ecf.icst.nbs.gov>
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Date: Tue, 14 Jun 88 08:18:37 -0400 (EDT)
From: David Greene <dg1v+@andrew.cmu.edu>
Subject: Re: Me, Karl, Stephen, Gilbert
In AIList Digest V7 #29, Stephen Smoliar writes:
> What have all those researchers who don't spend so much
> time with computer programs have to tell us?
I'm not advocating Mr. Cockton's views, but the limited literature breadth in
many AI papers *is* self-defeating. For example, until very recently, few
expert system papers acknowledged the results of 20+ years of psychology
research on Judgement and Decision Making. It seems odd that AI people
studying experts decision making would not reference behavioral/ performance
research on human/ expert decision making.
The works of Kahneman, Tversky, Hogarth and Dawes (to name some luminaries),
all identify inherent flaws in human (including experts') judgement. These
dysfunctional biases result in consistent suboptimal decision rules across many
realistic conditions (setting aside debates on "optimality"). Yet, AI
researchers and knowledge engineers attempt to produce fidelity to the expert
and compare the resultant system to the experts performance. Is it a wonder
that many ES's don't work in the field...
Perhaps a broader literature/ research exposure could be advantageous to AI (or
any field)...
-David
dg1v@andrew.cmu.edu
Carnegie Mellon
"You're welcome to use my oppinions, just don't get them all wrinkled..."
------------------------------
Date: Tue, 14 Jun 88 07:52:42 PDT
From: golden@frodo.STANFORD.EDU (Richard Golden)
Subject: Re: Definition of Information
In AILIST Digest V7 #26 Bruce Nevin asks:
Can anyone point me to a coherent definition of information respecting
information content, as opposed to merely "quantity of information"?
This question is really related to an earlier discussion concerned with
viewing probability theory as a measure of belief. We can think of a
knowledge structure as being represented by a probability distribution
which assigns some "degree of belief" (i.e., a probability) to some
set of events (i.e., a sample space). Let X be an event which occurs
with probability p(X). Then clearly an equivalent "knowledge structure"
which assigns some "degree of surprise" (i.e., -LOG[p(X)]) to some
set of events (i.e., a sample space) may be constructed.
The simple point which I am making is that the SAMPLE SPACE and the
STRUCTURE OF ITS ELEMENTS is a necessary component of the definition of
information in a technical sense and information CONTENT (for the most
part) resides in this SAMPLE SPACE.
Richard Golden (golden@psych)
------------------------------
Date: Tue, 14 Jun 88 10:42:12 bst
From: Ian Dickinson <ijd%otter.lb.hp.co.uk@RELAY.CS.NET>
Subject: Re: representation languages
/ otter:comp.ai.digest / vierhout@swivax.UUCP (Paul Vierhout) / writes:
> AIlanguage features:
> old: procedure-data equivalence
> less old: nondeterminism, 'streams'
> ,unification,OPS5 pattern matching,
> shell-like: ability to specify frames and/or rules, and possibly control
> promises: abstract models of cognitive tasks like the Interpretation Models
> of Breuker and Wielinga (SWI-UvA, Amsterdam) for knowledge acquisition,
> or the six generic tasks of Chandrasekaran (Ohio State Univ.).
> Not at all an exhaustive list; shouldn't an AIlanguage ideally exhaustively
> offer all features currently available ?
If you read the various papers from Chandresakaran's group, you will see that
one of their central hypotheses is that you cannot define a single language
that is usable to write all applications. Each generic task (and I think
there are rather more than six) will have its own language, which specialises
control and data structures to that task. In fact, they seem to anticipate
a spectrum of languages each individually suited to *part* of the application
being
What we absolutely *must* avoid in defining representation languages of the
future is the "good feature explosion" - ie adding new features like frames,
rules, backwards, forwards and side ways inference, 12 inheritiance schemes,
etc - simply because they could be useful in some circumstance.
This is the route to the KEE's and ART's ++ of future representation schemes.
Whilst I have no doubt that these systems are useful today, _I_ as an
application developer want to see a representation system that is maximally
small whilst giving me the power that I need. The philosophy I would like to
see adopted is:
o define conceptual representations that allow applications to be
written at the maximum level of abstraction (eg generic tasks)
o define the intermediate representations (frames, rules, sets ..)
that are needed to implement the conceptual structures
o choose a subset of these representations that can be maximally
tightly integrated with the base language of your choice (which
would not be Lisp in my choice)
By doing this, we can not only help the application developer by giving her
access to all of the abstraction power in the system, but also have a chance
of getting the semantics of these systems properly understood and defined.
++ KEE and Art are registered trademarks.
Ian.
+---------------------+--------------------------+------------------------+
|Ian Dickinson net: All opinions expressed |
|Hewlett Packard Labs ijd@otter.hplabs.hp.com are my own, and not |
|Bristol, England ijd@hplb.uucp necessarily those of |
|0272-799910 ..!mcvax!ukc!hplb!ijd my employer. |
+---------------------+--------------------------+------------------------+
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End of AIList Digest
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