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AIList Digest Volume 4 Issue 261
AIList Digest Wednesday, 19 Nov 1986 Volume 4 : Issue 261
Today's Topics:
Queries - PEARL AI Package & Contextual Knowledge and Multilayer Learning &
Logic Programming in APL & Cornell Synthesizer/Generator,
Literature - Books Available for Review,
Logic Programming - Nonmonotonic Reasoning and Truth Maintenance Systems,
Science Fiction - Sentient Computers,
Education - Cognitive Science Degree Programs,
Ethics - AI and the Arms Race
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Date: Thu, 13 Nov 86 14:25:45 est
From: rochester!tropix!dls@seismo.CSS.GOV (David L. Snyder )
Reply-to: tropix!dls@seismo.CSS.GOV (David L. Snyder )
Subject: pearl AI package
A few questions about pearl (Package for Efficient Access to
Representations in Lisp):
Can anyone tell me what, if any, activity is going on with pearl these
days? (Is the pearl-bugs mailing list still active?) Has anyone used
it for non-toy problems? Any chance it'll be ported into common
lisp? Is there something better that superceeds it (and is in the
public domain)?
Thanks!
P.S. Try tropix!dls@rochester as an arpa address if other alternatives fail.
------------------------------
Date: Wed, 12 Nov 86 13:50 ???
From: MUKHOP%RCSJJ%gmr.com@RELAY.CS.NET
Subject: Contextual Knowledge and Multi-layer Learning
I read with interest the abstract for Richard M. Keller's talk, "The Role
of Explicit Contextual Knowledge in Learning Concepts to Improve Performance"
(V4 #258), part of which is reproduced below:
> This dissertation addresses some of the difficulties encountered
> when using artificial intelligence-based, inductive concept learning
> methods to improve an existing system's performance. The underlying
> problem is that inductive methods are insensitive to changes in the
> system being improved by learning. This insensitivity is due to the
> manner in which contextual knowledge is represented in an inductive
> system. Contextual knowledge consists of knowledge about the context
> in which concept learning takes place, including knowledge about the
> desired form and content of concept descriptions to be learned (target
> concept knowledge), and knowledge about the system to be improved by
> learning and the type of improvement desired (performance system
> knowledge).
> ...
> To investigate the thesis, this study introduces an alternative
> concept learning framework -- the concept operationalization framework
> -- that requires various types of contextual knowledge as explicit
> inputs.
>...
Isn't this described in the literature as a two-layer learning system
(multi-layer in the general case) of which Samuel's checkers player is
one of the earliest examples? What are the differences, if any?
Uttam Mukhopadhyay
GM Research Labs
------------------------------
Date: Mon, 17 Nov 86 14:45 EST
From: McHale@RADC-MULTICS.ARPA
Subject: Logic programming in APL
A while ago I heard of a system (from John Hopkins, I think) that combined
logic programming with APL called APLLog. I would appreciate any pointers
anyone could give me concerning this language. (User comments, software
availability, underlying hardware, point of contact, etc.)
Michael L. Mc Hale
RADC/COES
Griffiss AFB, NY 13441-5700
arpa% McHale RADC-Multics
------------------------------
Date: Tue, 18 Nov 86 16:00:56 pst
From: Neil O'Neill <oneill@lll-tis-b.ARPA>
Subject: Cornell Synthesizer/Generator (Need help)
Does anyone have experience in running the Cornell Synthesizer/Generator?
We could use some help with it if you know how to use it.
Neil J. O'Neill
ARPA: oneill@lll-tis-b.ARPA
UUCP: {ihnp4,dual,sun}!lll-lcc!styx!oneill
------------------------------
Date: Tue, 18 Nov 86 08:01:20 -0500
From: sriram@ATHENA.MIT.EDU
Subject: Books available for review
The following books are available for review for the International
Journal of AI in Engineering. If you are interested in acquiring
a copy (and review it too), send mail to sriram@athena.mit.edu with
your US mailing address. Please note that I have only single copies
and books will be handed out on a first come basis.
Machine Interpretation of Line Drawing
Kokichi Sugihara
MIT Press
Introduction to Robotics. Mechanics and control.
J. J. Craig
Addison-Wesley
Parallel Distributed Processing Vol 1
J.L. McClelland, D.E. Runelhart and the PDP research group
MIT Press
Paralell Distributed Processing Vol 2
J.L. McClelland,D.E. Runelhart and the PDP research group
MIT Press
The acquisition of Syntactic Knowledge
R.C. Berwick
MIT Press
Computational Model of Discounts
Edited by M. Brady and R. Berwick
MIT Press
Artificial Inteligence.The very Idea.
J. Haugeland
MIT Press
Systems that learn
D.N. Osherson, M. Srob and S. Weinstein
MIT Press
Robot Motion. Planning and control.
Edited by M. Brady, J.M. Hollerbach,T.KL. Johnson, T. Lozano-Pevec
MIT Press
The measurement of Visual Motion
Gllen Catherine Hildreth
MIT Press
A Geometric Investigation of Reach
J.V. Korein
MIT Press
Robot Hands and the Mechanics of Manipulation
M.T. Mason, J.K. Salisbury Jr
MIT Press
Theory and Practice of Robots and Manipulations
Edited by A. Morecks,G. Bianchi and K. Kedziar
MIT Press
Robot Manipulators.Mathematics, Programming and Control
Richard P. Paul
MIT Press
Expert Systems: Techniques, Tools and Applications
P. Khalr and D. Waterman
Addison-Wesley
------------------------------
Date: Thu, 13 Nov 86 10:06:11 est
From: Randy Goebel LPAIG
<rggoebel%watdragon.waterloo.edu@RELAY.CS.NET>
Subject: Re: Non-monotonic reasoning and truth maintenance systems
> "These systems don't usually have any deductive power at all,
> they are merely constraint satisfaction devices."
> --David Etherington
>
> I am confused by this last sentence. Isn't constraint satisfaction
> a kind of inference? deKleer's ATMS and McAllester's RUP handle
> large portions (maybe all?) of propositional logic.
>
> --Tom Dietterich
If one views constraint satisfaction as incremental model elimination,
then there is a kind of inference going on, e.g., the number of models
for p(X) & q(X) is reduced by adding the new constraint r(X), to get
p(X) & q(X) & r(X). One can further see constraint satisfaction as
inference by looking at Prolog puzzle solutions, where a list of
constraints is posed as a goal, and the resolution prover must find
a satisfying substitution; there is search involved, but satisfying
substitutions are consequences of the axioms. Perhaps the best
intuition about ``truth maintenance''-like systems is that they provide
what is necessary for efficiently locating derivation steps that relied
on assumptions. It's probably natural that any actual implementation
blurs the distinction between the derivation maintenance and retrieval
subsystem, and the prover that actually applies the inference rules to
build derivations.
Randy Goebel
------------------------------
Date: 12 Nov 86 15:43:00 GMT
From: husc6!necntc!mirror!gabriel!inmet!sebes@eddie.mit.edu
Subject: Re: Canonical list of sentient computer
In the "sentient computer" class, there is Frank
Herbert's _Destination Void_, which I recall as
being notable not only for being a pretty good
novel, but also for not appearing at all ridiculous
or dated even 20-30 years after writing. In fact,
some of the ideas mentioned are more in style now than
then, or even a few years ago.
--John Sebes
------------------------------
Date: 12 Nov 86 16:03:00 GMT
From: husc6!necntc!mirror!gabriel!inmet!sebes@eddie.mit.edu
Subject: Re: choosing grad schools
Stanford has a program along the lines of that described
at UCSD. The participating departments are CS, linguistics,
philosophy, and psychology. There is a list of courses
offered in those departments that count toward a course
requirement for a phd in 'X and Cognitive Science' (I am
not sure that that is the wording, but it is the gist).
In addition to whatever course work you need to do in
your department, you must take some number of those
approved courses, with a certain distribution between
your dept and the other three. Depending on your dept
and how much course work you need to do there, it could
be quite an undertaking. Also, it is a relatively recent
thing, and I not sure how many people are actually
involved in it.
I found out about it simply by calling one of the depts
and asking if that had any cogsci organization.
Stanford also has a well-funded research center, the
Center for the Study of Language and Intelligence
(or something similar that spells CSLI ("Cicely")).
--John Sebes
------------------------------
Date: Sun, 16 Nov 86 23:22:58 PST
From: talmy%cogsci.Berkeley.EDU@berkeley.edu (Len Talmy)
Subject: Cognitive Science degree programs at UC Berkeley
In response to Don Norman's call for information, no, UC Berkeley does
not have any degree-granting program in Cognitive Science either at the
undergraduate or at the graduate level. So far, the most a student has
been able to do is to make use of the special institutional apparatus
for setting up a personally tailored degree program. However, we are
now actively working on setting up a degree program at the undergraduate
level. Even such a modest goal should take from one to two years,
after all the committees have been formed and have analyzed the proposal.
It was felt that a graduate degree program ought to be established only
after an undergraduate one was in place and after some demand for
Cognitive Science Ph.D.'s had developed. But the "Doctorate in X and
Cognitive Science" formula is an interesting intermediate possibility,
and we'll look into it.
Len Talmy (coordinator, cognitive science program)
talmy@cogsci.berkeley.edu
------------------------------
Date: Tue, 18 Nov 86 12:19:58 est
From: "B. Lindsay Patten" <shen5%watdcsu.waterloo.edu@RELAY.CS.NET>
Reply-to: "B. Lindsay Patten"
<shen5%watdcsu.waterloo.edu@RELAY.CS.NET>
Subject: Re: AI and the Arms Race
In article <LIN.12253338541.BABYL@XX.LCS.MIT.EDU> LIN@XX.LCS.MIT.EDU writes:
>[I posted a message from AILIST on ARMS-D, and got back this reply.]
>From: ihnp4!utzoo!henry at ucbvax.Berkeley.EDU
>Re: Professionals and Social Responsibility for the Arms Race
[some valid objections to arguments made by Dr. Weizenbaum on problems with AI]
>> 8) every researcher should assess the possible end use of
>> their own research, and if they are not morally comfortable
>> with this end use, they should stop their research...
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
>> He specifically referred to research in machine vision, which he
>> felt would be used directly and immediately by the military for
>> improving their killing machines...
>
>I'm afraid this is muddy thinking again. *All* technology has military
>applications.
[examples of good things that came out of military research]
>It's hard
>to conceive of a field of research which doesn't have some kind of military
>application.
>
> Henry Spencer @ U of Toronto Zoology
> {allegra,ihnp4,decvax,pyramid}!utzoo!henry
This is by far the most common objection I've heard since Dr. Weizenbaum's
lecture and one which I think avoids the point. Read the first three lines
of point 8 above. The real point Dr. Weizenbaum was trying to make (in my
opinion) was that we should weigh the good and bad applications of our work
and decide which outweighs the other. The examples that he gave were just
areas in which he personally believed the bad applications outweighed the
good. He was very explicit that he was just presenting HIS personal opinions
on the merits of these applications. Basically he said that if you feel
your work will do more harm than good you should find another area to work in.
My objection to his talk is that he seemed to want to weigh entire applications
against one another. It seems to me that we should be examining the relative
impact of our research in the applications which we approve of and in those we
object to.
Lindsay Patten
|Cognitive Engineering Group (519) 746-1299|
|Pattern Analysis and Machine Intelligence Lab lindsay@watsup|
|University of Waterloo {decvax|ihnp4}!watmath!watvlsi!watsup!lindsay|
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End of AIList Digest
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