LAWS@SRI-AI.ARPA (04/25/85)
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-AI>
AIList Digest Thursday, 25 Apr 1985 Volume 3 : Issue 53
Today's Topics:
Request - MRS Information,
Applications - Architecture & Agricultural AI,
Psychology - Emotional Attachment & Semantics of Humor,
Philosophy - Knowledge, Information, and Belief &
Knowledge as an Obstacle to Learning,
Application & Humor - BBoard Contest,
Seminars - Bertrand Constraint Language (SRI) &
Assumption-Based Truth Maintenance (SU)
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Date: 23 Apr 85 15:52:40 PST (Tue)
From: whiting@sri-spam
Subject: Request for additional information on MRS
I am looking at making some extensions/improvements to MRS.
The following are being investigated:
- Adding a better user-interface
- Improving efficiency
- Adding debugging aids
- Extending the system to deal with uncertainty elegantly
I have all the HPP reports on MRS, I am looking for additional information.
If you have worked with the system or know of articles which might be
useful to me, I would very much appreciate hearing from you.
Thanx in Advance,
Kevin Whiting
(415) 859-4099
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Date: 24 Apr 1985 1119-EST
From: Benoit Flamant <FLAMANT@CMU-CS-PS2.ARPA>
Reply-to: FLAMANT@CMU-CS-PS2.ARPA
Subject: Expert Systems in Architecture
I am looking for information about experts systems in the domain of
architecture.
Does anyone know of good articles or books published recently, understandable
by people without deep knowledge in AI ?
Please reply to flamant@cmu-cs-ps2. Thanks.
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Date: Sat 20 Apr 85 17:42:22-PST
From: LOUROBINSON@SRI-AI.ARPA
Subject: Agricultural AI
In response to Peter Friedland's inquiry regarding agricultural
AI systems:
The Imperial Chemical Industries of Great Britain recently
entered into an agreement with a British expert systems company,
ISIS Systems, to develop tools that will assist farmers. One of
these tools is a system called Counselor intended to help farmers
analyze crop diseases. The advisory service calculates the probable
incidence of disease based on data provided by the user. "Wheat
Counselor" can be used to determine probable wheat infestations and
appropriate (chemical) treatment.
Lou Robinson
The AI Report
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Date: 20 Apr 85 17:16 EST (Sat)
From: _Bob <Carter@RUTGERS.ARPA>
Subject: Midnight Theorizer
From: BATALI%MIT-OZ at MIT-MC.ARPA
From: MINSKY
Perhaps this, too, explains the prolonged, mourning-like
depression that follows sexual or other forms of personal
assault. No matter that the unwelcome intimacy of violence
may be brief; it nonetheless affects one's attachment
machinery, however much against one's wish.
So the suggestion is that the rape-victim feels bad because she has
formed an attachment-bond to her attacker? The same "mechanism" is
involved as in the formation of her attachment-bonds to other people?
That is precisely the suggestion.
So she feels bad not because she has been raped, but because her
rapist has then left her? Is there a shred of evidence that any rape
victim has ever felt this way?
No, perhaps the victim feels bad because of
a. The terrible invasion of the sexual assault itself,
b. The cognitive dissonance when the attachment machinery begins
to operate in these terribly inappropriate circumstances.
I suspect that many people would agree there is more than a shred of
evidence for similar emotive patterns. The syndrome in which
hostages identify with their captors, despite violence (and in the
case of Patty Hearst, rape) comes to mind.
Is this theory somehow suggesting that
there really isn't much of a difference between rape and seduction and
falling in love?
Perhaps not, in some ways.
Is it being assumed that fear, pain and loss of
self-esteem is not enough to "explain the prolonged depression" that
follows sexual assault?
No, rather it seems to be examining the internal dynamics of "loss of
self-esteem."
I have some doubts about that part of AI which asserts the validity
of scientific inquiry that gathers "data" by introspection. But I
have even greater doubts about moral indignation as a criterion for
rejection of hypotheses (or of humor, for that matter).
_B
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Date: Sun, 21 Apr 85 11:51 EST
From: Brant Cheikes <Brant%upenn.csnet@csnet-relay.arpa>
Subject: Book on semantics of humor
Since there was some recent mention on studies of humor, I thought
I'd mention a book I just started reading on that very topic:
"Semantic Mechanisms of Humor"
Raskin, Victor
D. Reidel Publishing Company
Dordrecht, Holland, 1985.
Raskin attempts to develop a semantic theory that captures the
necessary and sufficient conditions for a text to be considered
funny by the "native speaker." The book is full of examples,
however, in the preface, Raskin insists that the book is not a
joke book, rather, that all joke examples were chosen purely for
their illustrative value. So if you want to know what's funny
and what's not and why, then read this book.
Brant
------------------------------
Date: Mon, 22 Apr 85 11:04:49 EST
From: Morton A Hirschberg <mort@BRL-BMD.ARPA>
Subject: Re: Jeff Peck
Jeff's got a good start on the data, information, knowledge hierarchy (you see
it here as you read from left to right, think from bottom to top). Data is all
around us and can exist without context. Information is derived from data in a
particular context with or without the aid of data, information, and knowledge
from other contexts. From information we can derive secondary data. Think of
the two triplets of numbers representing the coordinates of two points in three
space. Each by itself is meaningless however, assuming that the triplets are
not identical, one can derive the equation of a line in space. From that
equation, one can then derive as many new triplets as one desires (some may
actually be useful). Knowledge can be derived from information, that is it is
the synthesis of information (usually thought of in particular contexts).
Thinking about the hierarchy in this way has been quite useful in dealing
with and teaching data basing. We also see that data which can not be
manipulated to form information remains data. The listing of names, street
numbers and telephone numbers in a telephone book is really data and those
books should be called data books and not information books. There are ways
of manipulating those data (I don't work for Ma Bell) to derive information
(Ma Bell sells those books to businesses) but that is another story.
Mort
------------------------------
Date: Mon, 22 Apr 85 10:36:39 EST
From: cugini@NBS-VMS
Subject: definition of knowledge/information/data
Alright, my philosophical feathers have been ruffled...
"True justified belief" is *not* a special case of "things that are
useful in making good decisions".
1. While it probably is true as a matter of empirical fact that true
beliefs are likely to be more useful for making decisions than
are false ones (in most cases), this is certainly not true by
definition.
2. One quick counter-example: Suppose you were in a prisoner-of-war
camp. You might have a false, unjustified belief that you would
soon be rescued. This irrational hope might in fact have greater
survival value (= lead to better decisions on how to act) than a
more realistic outlook - but the utility of the belief hardly
makes it true, in the any normal English sense of the word.
3. Anyway, the emphasis of the "true justified belief" concept is on
"justified" - ie defining knowledge as a true belief rationally
arrived at, rather than as a lucky guess. There are problems with
this defintion, to be sure, in particular, distinguishing between
subjective justification (I believe X, based on the evidence given
to me so far), vs objective (but in fact part of that evidence consists
of lies, undetected by you).
A typical case discussed is: suppose Mr. X wrongly believes that P,
and, wanting to deceive you, tells you that not-P is the case (which
in fact it is). You then, believing him, have a true belief that
not-P is so. But is it justified? Subjectively, yes, because you
are acting rationally - but in fact you're relying on a method
(Mr. X) which is unreliable - if P really were the case, this method
would not lead you to believe P - so your source of belief is not
related to its object in such a way that it would reliably track that
object in other "nearby" possible worlds.
Robert Nozick in "Philosophical Questions" has a very
well-written insightful discussion on all this.
John Cugini <Cugini@NBS-VMS>
National Bureau of Standards
Bldg 225 Room A-265
Gaithersburg, MD 20899
phone: (301) 921-2431
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Date: Wed, 17 Apr 85 11:24:58 pst
From: Vaughan Pratt <pratt@Navajo>
Subject: Knowledge as an obstacle
[Forwarded from the Stanford bboard by Laws@SRI-AI.]
This morning I overhead "I just don't understand Karl Marx" as I biked
past two students. My first reaction was "Gee, if they think Marx is
tough they must go bananas with Kant." Then on further reflection
I thought "Now if Marx is really that inaccessible, where did he
get such a large following?" Which train of thought led me to:
There are two very different reasons for being unable to grasp an
idea. The "obvious" one is that it takes time to assimilate new
ideas. The less obvious one is that you may already know too much! If
the new idea is inconsistent with what you know, something has to
give.
Now consider the following scenario. A teacher of Marx spends say forty
years expounding Marx's ideas. In his youth he has no trouble getting
the message across. Later he finds it much harder. He agonizes: "Are
students really getting dumber, or am I just losing my touch?"
The truth of the matter may be neither. He and his students may simply
have diverging theories of the world. His stays put while theirs
(collectively!) continue to accumulate the latest ideas. The more
divergent those theories become, the harder he finds it to get his
ideas across.
What really ices all this is that neither he nor his students diagnose
the problem. They all think that there is an idea here which the
students are just having trouble absorbing. If the teacher were to say
"Marx's ideas are contradicted by X,Y,Z that you take as economic
gospel" then the students would know what knowledge had to be laid
aside to appreciate Marx. This is surely better than laying aside
either nothing, everything, or a guessed-at selection.
Whether teaching Marx, or any other subject, actually works this way I
haven't a clue. Educational theorists have a batting average about that
of economic theorists, whether you look at the professional leagues or
the amateur.
-v
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Date: 21 Apr 85 08:32:45 EST
From: Robert.Thibadeau@CMU-RI-VI
Subject: BB Contest
[Forwarded from the CMU bboard by Laws@SRI-AI.]
Bulletin boards certainly have had their ups and downs. I have always
objected to a plethora of boards and to a plethora of posts, a quandary
perhaps. But let us invite an "expert system" contest in the world
community (for heavens sake!) which provides us with "the intelligent
bulletin board". I can indicate my own predilections, and, when I write a
message, the system will interpret it with respect to the world of
everybody's predilections. Anyone can enter: protocols are at your finger
tips. Imagine a system which, after you post your message says, "System
won't bother on that post, no one wants to read it." You might even ask
why, and find out. Then imagine the thrill, one day, of seeing "System
has decided everybody in the world wants that message today -- automatic
phoning system engaged." Frabjous joy. This contest is serious: when you
have a system design, describe it: consider performance, compatibility,
and extensibility along with representational and procedural intelligence.
Deadline is December 1, 1985 (mid-term assignments anyone?). Mail
description only to prism@cmu-ri-vi. I will put my IRS gift of $100 into a
winner and invite other sufferers longing for the good old days to do the
same (send commitments not cash). All suggestions will be publicly
available, the results published (SIGART Newsletter).
------------------------------
Date: 24 Apr 1985 0959-PST
From: GOGUEN@SRI-CSL.ARPA
Subject: Seminar - Bertrand Constraint Language (SRI)
CSL SEMINAR, 10:30am THURSDAY, 25 APRIL 1985, ROOM EL381
-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
Bertrand, a General Purpose Constraint Language
Wm Leler
Computer Research Laboratory
Tektronix, Inc.
Constraint languages and constraint satisfaction techniques are
making the problem solving abilities of the computer available
to a wider audience. For example, simple spread-sheet languages
such as VisiCalc allow many different financial modeling
problems to be solved without resorting to programming. In a
conventional language the programmer must specify a step-by-step
procedure for the language interpreter to follow. In a
constraint language, programming is a descriptive task. The
user specifies a set of relationships, called constraints, and
it is up to the constraint satisfaction system to satisfy these
constraints. Unfortunately, constraint satisfaction systems
have been very difficult to build.
Bertrand is a general purpose language designed for building
constraint satisfaction systems. Constraints are solved using
rewrite rules, which are invoked by pattern matching. Bertrand
is similar in expressive power to relational languages such as
Prolog, but without any procedural semantics. Its lack of
procedural semantics makes Bertrand especially attractive for
execution on parallel processors.
This talk will review several example constraint satisfaction
systems built using Bertrand with applications in graphics,
design, and modeling. There will also be some discussion of the
language issues involved in the design of Bertrand.
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Date: Tue 23 Apr 85 13:19:28-PST
From: Carol Wright/Susie Barnes <WRIGHT@SUMEX-AIM.ARPA>
Subject: Seminar - Assumption-Based Truth Maintenance (SU)
SIGLUNCH
DATE: Friday, April 26, 1985
LOCATION: Chemistry Gazebo, between Physical &
Organic Chemistry
TIME: 12:05
SPEAKER: Johan Dekleer
Member of Research Staff in Qualitative
Physics at Xerox Park
TITLE: An Assumption-Based Truth Maintenance System
This talk presents a new view of problem solving motivated by a
new kind of truth maintenance system. Unlike previous truth maintenance
systems which were based on manipulating justifications, this truth
maintenance system is, in addition, based on manipulating assumption
sets. As a consequence it is possible to work effectively and
efficiently with inconsistent information, context switching is free,
and most backtracking (and all retraction) is avoided. These
capabilities motivate a different kind of problem-solving architecture
in which multiple potential solutions are explored simultaneously. This
architecture is particularly well-suited for tasks where a reasonable
fraction of the potential solutions must be explored.
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End of AIList Digest
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