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AIList Digest Volume 1 Issue 109
AIList Digest Monday, 5 Dec 1983 Volume 1 : Issue 109
Today's Topics:
Expert Systems & VLSI - Request for Material,
Programming Languages - Productivity,
Editorial Policy - Anonymous Messages,
Bindings - Dr. William A. Woods,
Intelligence,
Looping Problem,
Pattern Recognition - Block Modeling,
Seminars - Programs as Predicates & Explainable Expert System
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Date: Sun, 4 Dec 83 17:59:53 PST
From: Tulin Mangir <tulin@UCLA-CS>
Subject: Request for Material
I am preparing a tutorial and a current bibliography, for IEEE,
of the work in the area of expert system applications to CAD and computer aided
testing as well as computer aided processing. Specific emphasis is
on LSI/VLSI design, testing and processing. I would like this
material to be as complete and as current as we can all make. So, if you
have any material in these areas that you would like me to include
in the notes, ideas about representation of structure, knowledge,
behaviour of digital circuits, etc., references you know of,
please send me a msg. Thanks.
Tulin Mangir <cs.tulin@UCLA-cs>
(213) 825-2692
825-4943 (secretary)
------------------------------
Date: 29 Nov 83 22:25:19-PST (Tue)
From: sri-unix!decvax!duke!mcnc!marcel@uiucdcs.UUCP (marcel )@CCA
Subject: Re: lisp productivity question - (nf)
Article-I.D.: uiucdcs.4197
And now a plug from the logic programming people: try prolog for easy
debugging. Though it may take a while to get used to its modus operandi,
it has one advantage that is shared by no other language I know of:
rule-based computing with a clean formalism. Not to mention the ease
of implementing concepts such as "for all X satisfying P(X) do ...".
The end of cumbersome array traversals and difficult boolean conditions!
Well, almost. Not to mention free pattern matching. And I wager that
the programs will be even shorter in Prolog, primarily because of these
considerations. I have written 100-line Prolog programs which were
previously coded as Pascal programs of 2000 lines.
Sorry, I just couldn't resist the chance to be obnoxious.
------------------------------
Date: Fri, 2 Dec 83 09:47 EST
From: MJackson.Wbst@PARC-MAXC.ARPA
Subject: Lisp "productivity"
"A caveat: Lisp is very well suited to the nature of game programs.
A fair test would require that data processing and numerical analysis
problems be included in the mix of test problems."
A fair test of what? A fair test of which language yields the greatest
productivity when applied to the particular mix of test problems, I
would think. Clearly (deepfelt theological convictions to the contrary)
there is NO MOST-PRODUCTIVE LANGUAGE. It depends on the problem set; I
like structured languages so I do my scientific programming in Ratfor,
and when I had to do it in Pascal it was awful, but for a different type
of problem Pascal would be just fine.
Mark
------------------------------
Date: 30 Nov 83 22:49:51-PST (Wed)
From: pur-ee!uiucdcs!uicsl!Anonymous @ Ucb-Vax
Subject: Lisp Productivity & Anonymous Messages
Article-I.D.: uiucdcs.4245
The most incredible programming environment I have worked with to date is
that of InterLisp. The graphics-based trace and break packages on Xerox's
InterLisp-D (not to mention the Lisp editor, file package, and the
programmer's assistant) is, to say the least, addictive. Ease of debugging
has been combined with power to yield an environment in which program
development/debugging is easy, fast and productive. I think other languages
have a long way to go before someone develops comparable environments for
them. Of course, part of this is due to the language (i.e., Lisp) itself,
since programs written in Lisp tend to be easy to conceptualize and write,
short, and readable.
[I will pass this message along to the Arpanet AIList readers,
but am bothered by its anonymous authorship. This is hardly an
incriminating message, and I see no reason for the author to hide.
I do not currently reject anonymous messages out of hand, but I
will certainly screen them strictly. -- KIL]
------------------------------
Date: Thu 1 Dec 83 07:37:04-PST
From: C.S./Math Library <LIBRARY@SU-SCORE.ARPA>
Subject: Press Release RE: Dr. William A. Woods
[Reprinted from the SU-SCORE bboard.]
As of September 16, Chief Scientist directing all research in AI and related
technologies for Applied Expert Systems, Inc., Five Cambridge Center,
Cambridge, Mass 02142 (617)492-7322 net address Woods@BBND (same as before)
HL
------------------------------
Date: Fri, 2 Dec 83 09:57:14 PST
From: Adolfo Di-Mare <v.dimare@UCLA-LOCUS>
Subject: a new definition of intelligence
You're intelligence is directly proportional to the time it takes
you to bounce back after you're replaced by an <intelligent> computer.
As I'm not an economist, I won't argue on how intelligent we are...
Put in another way, is an expert that builds a machine that substitutes
him/er intelligent? If s/he is not, is the machine?
Adolfo
///
------------------------------
Date: 1 Dec 83 20:37:31-PST (Thu)
From: decvax!bbncca!jsol @ Ucb-Vax
Subject: Re: Halting Problem Discussion
Article-I.D.: bbncca.365
Can a method be formulated for deciding whether or not your are on the right
track? Yes. It's call interaction. Ask someone you feel you can trust about
whether or not you are getting anywhere, and to offer any advice to help you
get where you want to go.
Students do it all the time, they come to their teachers and ask them to
help them. Looping programs could decide that they have looped for as long
as they care to and reality check them. An algorithm to do this is available
if anyone wants it (read that to mean I will produce one).
--
[--JSol--]
JSol@Usc-Eclc/JSol@Bbncca (Arpa)
JSol@Usc-Eclb/JSol@Bnl (Milnet)
{decvax, wjh12, linus}!bbncca!jsol
------------------------------
From: Bibbero.PMSDMKT
Reply-to: Bibbero.PMSDMKT
Subject: Big Brother and Block Modeling, Warning
[Reprinted from the Human-Nets Digest.]
[This application of pattern recognition seems to warrant mention,
but comments on the desirability of such analysis should be directed
to Human-Nets@RUTGERS. -- KIL]
The New York Times (Nov 20, Sunday Business Section) carries a warning
from two Yale professors against a new management technique that can
be misused to snoop on personnel through sophisticted mathematical
analysis of communications, including computer network usage.
Professors Scott Boorman, a Yale sociologist, and Paul Levitt,
research mathematician at Yale and Harvard (economics) who authored
the article also invented the technique some years ago. Briefly, it
consists of computer-intensive analysis of personnel communications to
divide them into groups or "blocks" depending on who they communicate
with, whom they copy on messages, who they phone and who's calls don't
they return. Blocks of people so identified can be classified as
dissidents, potential traitors or "Young Turks" about to split off
their own company, company loyalists, promotion candidates and so
forth. "Guilt by association" is built into the system since members
of the same block may not even know each other but merely copy the
same person on memos.
The existence of an informal organization as a powerful directing
force in corporations, over and above the formal organization chart,
has been recognized for a long time. The block analysis method
permits and "x-ray" penetration of these informal organizations
through use of computer on-line analysis which may act, per the
authors, as "judge and jury." The increasing usage of electronic
mail, voice storage and forward systems, local networks and the like
make clandestine automation of this kind of snooping simple, powerful,
and almost inevitable. The authors cite as misusage evidence the high
degree of interest in the method by iron curtain government agencies.
An early success (late 60's) was also demonstrated in a Catholic
monastery where it averted organizational collapse by identifying
members as loyalists, "Young Turks," and outcasts. Currently,
interest is high in U.S. corporations, particularily the internal
audit departments seeking to identify dissidents.
As the authors warn, this revolution in computers and information
systems bring us closer to George Orwell's state of Oceania.
------------------------------
Date: 1 Dec 1983 1629-EST
From: ELIZA at MIT-XX
Subject: Seminar Announcement
[Reprinted from the MIT-AI bboard.]
Date: Wednesday, December 7th, l983
Time: Refreshments 3:30 P.M.
Seminar 3:45 P.M.
Place: NE43-512A (545 Technology Square, Cambridge)
PROGRAMS ARE PREDICATES
C. A. R. Hoare
Oxford University
A program is identified with the strongest predicate
which describes every observation that might be made
of a mechanism which executes the program. A programming
language is a set of programs expressed in a limited
notation, which ensures that they are implementable
with adequate efficiency, and that they enjoy desirable
algebraic properties. A specification S is a predicate
expressed in arbitrary mathematical notation. A program
P meets this specification if
P ==> S .
Thus a calculus for the derivation of correct programs
is an immediate corollary of the definition of the
language.
These theses are illustrated in the design of two simple
programming languages, one for sequential programming and
the other for communicating sequential processes.
Host: Professor John V. Guttag
------------------------------
Date: 12/02/83 09:17:19
From: ROSIE at MIT-ML
Subject: Expert Systems Seminar
[Forwarded by SASW@MIT-MC.]
DATE: Thursday, December 8, 1983
TIME: 2.15 p.m. Refreshments
2.30 p.m. Lecture
PLACE: NE43-AI Playroom
Explainable Expert Systems
Bill Swartout
USC/Information Sciences Institute
Traditional methods for explaining programs provide explanations by converting
the code of the program to English. While such methods can sometimes
adequately explain program behavior, they cannot justify it. That is, such
systems cannot tell why what the system is doing is reasonable. The problem
is that the knowledge required to provide these justifications was used to
produce the program but is itself not recorded as part of the code and hence
is unavailable. This talk will first describe the XPLAIN system, a previous
research effort aimed at improving the explanatory capabilities of expert
systems. We will then outline the goals and research directions for the
Explainable Expert Systems project, a new research effort just starting up at
ISI.
The XPLAIN system uses an automatic programmer to generate a consulting
program by refinement from abstract goals. The automatic programmer uses two
sources of knowledge: a domain model, representing descriptive facts about the
application domain, and a set of domain principles, representing
problem-solving knowledge, to drive the refinement process forward. As XPLAIN
creates an expert system, it records the decisions it makes in a refinement
structure. This structure is then used to provide explanations and
justifications of the expert system.
Our current research focuses on three areas. First, we want to extend the
XPLAIN framework to represent additional kinds of knowledge such as control
knowledge for efficient execution. Second, we want to investigate the
compilation process that moves from abstract to specific knowledge. While it
does seem that human experts compile their knowledge, they do not always use
the resulting specific methods. This may be because the specific methods
often contain compiled-in assumptions which are usually (but not always)
correct. Third, we intend to use the richer framework provided by XPLAIN for
enhanced knowledge acquisition.
HOST: Professor Peter Szolovits
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End of AIList Digest
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