LAWS@SRI-AI.ARPA (08/01/85)
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-AI>
AIList Digest Thursday, 1 Aug 1985 Volume 3 : Issue 102
Today's Topics:
Queries - PRESS & Loglan,
Linguistics - Aymara,
Expert Systems - Definition,
Games - Chess Programs and Cheating,
AI Tools - POPLOG
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Date: Thu, 25 Jul 85 10:08 EST
From: D E Stevenson <dsteven%clemson.csnet@csnet-relay.arpa>
Subject: Information on PRESS
I would like to get a copy of PRESS. Can anyone tell me
how to obtain one?
PRESS is the name of the symbolic algebra system that he developed
at Edinburgh. I have read spots here and there about it, mostly in
the applied math literature. It is written in PROLOG and is
reputed to be very fast. I asked for PROLOG-based systems on the
symalg net; PRESS was the only system identified.
I am interested in functional/logic programming and numerical analysis;
I thought I might get a copy and see what I could do with it.
Steve Stevenson
(803) 656-5880
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Date: Sun 28 Jul 85 18:11:09-PDT
From: FIRSCHEIN@SRI-AI.ARPA
Subject: Loglan
LOGLAN was (is?) a language designed to test the Sapir-Whorf
hypothesis that the natural languages limit human thought.
The Loglan Institute was set up to publish books on the
subject and to carry out investigations in loglan.
Does anyone know whether the Loglan Institute still exists
and what has been done with loglan? Does anyone have a current
address for them?
[The most recent address I have is The Loglan Institute, Inc.,
2261 Soledad Rancho Road, San Diego, CA 92109. -- KIL ]
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Date: Mon 29 Jul 85 10:59:04-PDT
From: Ken Laws <Laws@SRI-AI.ARPA>
Subject: Aymara
Robert Van Valin ("ucdavis!harpo!lakhota"@BERKELEY) sent me a clipping
from the SSILA Newsletter. It's a letter from Dr. M.J. Hardman-de-Bautista,
Director of the Aymara Language Materials Program, stressing that
Ivan Guzman de Rojas is not associated with the ALMP, does not himself
speak Aymara, and bases his work in machine translation on a grammar
and dictionary written over 400 years ago by a Jesuit priest. He claims
that Mr. Guzman's published examples of Aymara are nearly all grammatically
incorrect and that the stated meanings for acceptable sentences are
often wildly inaccurate. "His poor understanding of Aymara word and
sentence structure results in forms that are simply unintelligible to
the Aymara." Which is not to say that Guzman's translation program
can't work, but it does cast a suspicious light on the matter.
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Date: 30 Jul 85 15:38 PDT
From: Miller.pasa@Xerox.ARPA
Subject: Defining the Expert System
I am spending this summer as an intern for Xerox AI Systems group where
part of my task is to come up with a working definition of what
constitutes an "Expert System." Having done some rather extensive
reading on AI in general and expert systems in particular throughout the
past month, I have come to two conclusions:
First, due perhaps to media hype, the term "expert system" tends to get
bantered about extremely loosely and broadly and is applied to a wide
variety of programs and packages.
Second, the only definitions which seem to exist in testbooks,
articles, or company literature all seem to go something like this: "An
expert system is a computer program which does what an expert does."
While this definition is basic, I would like some more detail. So
here's the question: What do you, as a knowledgeable person in the field
of AI, consider to be the necessary minimum attributes for an "Expert
System?" Is it fair to give the same title to both CADUCEUS and to
'Tell Me Doctor' from Apple? Why or why not? Can you build an "Expert
System" with ART? How about TOPSI from Dynamic Master Systems (1000
rules maximum, forward-chaining, $75) ? How many rules does it take to
make a system 'expert'? What kind (and how large) of a domain must an
"expert system" address? Etc.
If you've got (or would care to write) a working definition of your own,
I'd love to hear it. Otherwise, I'd really appreciate your thoughts on
any of the above questions or any others that may come to mind.
Pointers towards reading sources probably wouldn't hurt. Look at this
as a very informal survey of the field-- linguistically speaking, a term
can only be defined by those who use it.
If anybody's interested, I'll be glad to compile the results and send a
copy.
Please reply to me at
Miller.pasa@Xerox.ARPA
--Chris Miller
[Alex Goodall supplies the following definitions in The Guide to
Expert Systems (published by Learned Information):
An expert system is a computer system that performs functions
similar to those normally performed by a human expert.
An expert system is a computer system that uses a representation
of human expertise in a specialist domain in order to perform
functions similar to those normally performed by a human expert
in that domain.
An expert system is a computer system that operates by applying
an inference mechanism to a body of specialist expertise
represented in the form of 'knowledge'.
He prefers the latter, but discusses all three in his first chapter.
Feigenbaum, in Knowledge Engineering for the 1980's (quoted by
Gevarter in An Overview of Expert Systems and by Kolbus and Mazzetti
in Artificial Intelligence Emerges) says:
An 'expert system' is an intelligent computer program that uses
knowledge and inference procedures to solve problems that are
difficult enough to require significant human expertise for their
solution. The knowledge necessary to perform at such a level,
plus the inference procedures used, can be thought of as a model
of the expertise of the best practitioners of the field.
The knowledge of an expert system consists of facts and heuristics.
The 'facts' constitute a body of information that is widely shared,
publicly available, and generally agreed upon by experts in a
field. The 'heuristics' are mostly private, little-discussed
rules of good judgement (rules of plausible reasoning, rules of
good guessing) that characterize expert-level decision making
in the field. The performance level of an expert system is
primarily a function of the size and quality of the knowledge base
that it possesses.
I don't care for the words "intelligent" and "difficult" in the first
paragraph, but the intention is clear.
As for size, expert systems for process control (e.g., using fuzzy
logic or qualitative "derivatives") can be quite small. I remember
a news note in Expert Systems (a journal from Learned Information)
about a system with 7 rules that was said to function well. -- KIL]
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Date: Sun 28 Jul 85 15:11:41-EDT
From: Oolong <WESALUM.A-LIAO-85@KLA.WESLYN>
Reply-to: LIAO%Weslyn.Bitnet@WISCVM.ARPA
Subject: More on Chess Programs and Cheating
In reading Dr. Laws objection, let me begin by saying that I
certainly agree that programs are better chess machines than
people are. Further, I agree that superior memory and speed in a
computer does NOT give a program an unfair advantage.
But perhaps I should clarify my position a bit more: I
believe that chess programs with moves written INTO the program
cheat in the sense that they will ALWAYS carry around ENCODED
(and thus represented) moves. Human players do not, on the whole,
do any such thing. Perhaps it would be best to try a Searleian
approach to the problem. In particular, you might be right about
the way humans play chess...we may have some moves memorized and
yet not always have them actively represented. Perhaps to some
extent, these might one of (or at least part of) Searle's
unconcious Intentional states. However, I'm not convinced of
that this position completely accounts for the way we play.
Consider players who are familiar with each other's form of
play. One cannot store every move made in every game played and
associate each game with the correct player (that goes for
programs as well). Still one recognizes particular COMBINATIONS
of moves ("chunking" a la Hofstadter) through experience of
following the other player's games and, moreover, direct play
reinforces those experiences. As Searle would put it - these
experiences/practices create capacities presumably realized as
neural pathways (a sort of learning, if you will). So in effect,
the "practiced moves" become part of the background and never
become embedded/encoded representations. This background only
creates the capacity to create the representations needed to
decide what move to make (i.e. to recognize a pattern of moves
made and then decide what moves are needed thwart such a
strategy). Certainly, if one chooses to memorize particular
moves, that is one's perogative, but on a whole, we don't do
that. If you will notice, this is the reason I argued for the
notion of "playing from our own experiences". This position that
I hold has the implication that we recognize strategies by the
results of our experience and so it is actually a part of us. I
think the interpretation of "run what ya brung" does not escape
the problem of the program playing by its author's experiences
and not its own.
Now let's consider the situation where two players
are not familiar with each other's form of play. Certainly,
there can be no pre-memorized set of optimal opening moves since
you have no experience with this player's strategic tendancies.
Yet, how is it that you open with your favorite move when you do
not know what else to do. Do you do it thinking "This is the
right move to make", or do you just move from experience?
How is it then you decide on what strategy to use? Presumably,
it makes more sense, perhaps, to say that we use memorized moves
going into such a game but use our background (thus experience)
to recognize what the other person is doing. In this way a human
player can "probe" the other player's strategy, though this
probing technique may be an inefficient way of deciding the
optimal strategy. However, this relies on experience and again,
a computer with built in moves cannot "probe" if it MUST to rely
on built-in moves (i.e. experiences not its own). In fact, this
is a form of learning and the acquirement of experience (a la
Searle). Personally, I do not see how my position differs from
Mr. Jennings - I too believe that a computer should "learn how to
play chess" before it is allowed to play in a tournament rather
than rely on moves ENCODED into the program. I see one major
problem however - one may keep entire games on disk/tape for use
later on in other tournaments with other players but after a
while you may exceed disk/tape memory. One may object by saying,
"Well, we could get a program to convenietly forget certain moves
(etc) and install the better ones." My problem with that
response is the question "What constitutes moves to be
forgotten?" Presumably, all this is a question of
Intentionality. After reading Searle's chapter on the
"Background" (from "Intentionality") I am beginning to suspect
that we may just forget the details of particular capacities and
retain some sort of skeletal structure of that capacity (whatever
that maybe). Just what is forgotten and how it is forgotten is
a question I offer to the forum for consideration.
- drew liao
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Date: 23 Jul 1985 23:58:11-BST
From: Aaron Sloman <aarons%svgv@ucl-cs>
Subject: POPLOG - A mixed language development system.
[Forwarded from the Prolog Digest by Laws@SRI-AI.]
Poplog is available on VAX and DEC 8600 computers.
It includes Prolog (compiled to machine code), Common Lisp (large
subset ready now, remainder available early 1986), POP-11
(comparable in power to Common Lisp, but uses a PASCAL-like syntax),
VED an integrated multi-window multi-buffer screen editor, which can
be used for all interactions with programs, operating system
utilities, online help, program libraries, teaching libraries, etc.
VED includes 'compile this procedure' 'compile from here to here'
'splice output into current file' etc.)
Incremental compilers are provided for Prolog, Lisp, and
POP-11. All the languages compile to the same intermediate
POPLOG 'Virtual machine' language, which is then compiled
to machine code. The 'syscompile' facilities make it easy
to add new front end compilers for additional languages,
which all share the same back-end compiler, editor and
environmental facilities. Mixed language facilities allow
sharing of libraries without re-coding and also allow
portions of a program to be written in the language which
is most suitable.
Approximate recent Prolog benchmarks, for naive reverse test,
without mode declarations:
VAX/780 + VMS 4.2 KLIPS
VAX/750 + Unix 4.2 2.4 KLIPS (750+Systime accelerator)
DEC 8600 13.0 KLIPS
SUN2 + Unix 4.2 2.5 KLIPS (also HP 9000/200)
GEC-63 + Unix V approx 6 KLIPS
The Prolog is being substantially re-written, for greater
modularity and improved efficiency. Mode declarations should
be available late 1985, giving substantial speed increase.
POP-11 and Common Lisp include both dynamic and lexical scoping,
a wide range of data-types, strings, arrays, infinite precision
arithmetic, hashed 'properties', etc. (Not yet packages, rationals
or complex numbers.) POP-11 includes a pattern-matcher (one-way
unification) with segment variables and pattern-restrictors.
External_load now allows 'external' modules to be linked in and
unlinked dynamically (e.g. programs written in C, Fortran, Pascal,
etc.). This almost amounts to a 'rapid prototyping' incremental
compiler for such languages.
A considerable number of AI-projects funded by the UK Alvey
Programme in universities and industry now use a mixture of
Prolog and POP-11, within Poplog.
Enquiries:
UK Educational institutions:
Alison Mudd,
Cognitive Studies Programme,
Sussex University,
Brighton, England. 0273 606755
-- Aaron Sloman
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End of AIList Digest
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