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AIList Digest Volume 3 Issue 098
AIList Digest Friday, 26 Jul 1985 Volume 3 : Issue 98
Today's Topics:
Queries - Lisp for Commodore 128 & AI Management & CS Taxonomy &
AI Databases & Geometry Survey & Space Planning,
AI Tools - ITP & Symbolics LISP/PROLOG,
Programming Languages - Interlisp Comments,
Games - Psychological Strategies
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Date: 22 Jul 85 10:42 EDT
From: Emanuel.henr@Xerox.ARPA
Subject: Lisp for Commodore 128 machine.
I have been reading this list for some time, and have found it quite
informative. I have also been impressed by the informed level of the
discussion. I would like to draw upon this now.
I just purchased the new Commodore 128 machine. It can run CPM-80, and
read IBM System 34 format disks (& Kaypro, Osborn disks). I would like
to know which of the LISP Packages that are available in this format
are the best to get. There seems to be a wide spred of prices across
the offered LISPs. Are the expensive ones that much better ? Is one
Outstanding ? Is one a best compromise of price and power ?
I thank you in advance for your response.
Keith j. Emanuel
Xerox/Human Factors.
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Date: Mon, 22 Jul 85 11:11:07 edt
From: simmons@EDN-VAX (Bob Simmons)
Subject: DCA Query on AI Management
At the Defense Communications Agency, we have been laying the
groundwork for an in-house AI group, primarily to test and evaluate
emerging expert system technology. We are also considering the
possibility of expanding to in-house development within the next three
to five years. I'm interested in the issues and specific problems that
other organizations have faced or expect to face when forming an
in-house group. I expect that these problems are quite different from
the concerns of a corporation developing a commercial product. In
particular, other than questions about the best hardware/software
combination, our concerns center on careful selection of a problem
domain, management of AI pilot projects, and justification of the
effort to upper-level management. As an aside, I found David Prerau's
"Selection of an Appropriate Domain for an Expert System" in the latest
issue of AI Magazine to be a great springboard into a pool of important
questions. We plan on using that article as a guideline for our own
interviews with our technical managers.
I'd appreciate any input that you have on this matter. If you are going
to be at IJCAI, please drop me a quick note and I'll look you up sometime
during that week. If not, please respond via electronic mail. If the
response warrants a summary (hopefully it will), I'll send a synopsis of
the interesting/important observations to AILIST.
Bob Simmons
Automated Technologies Planning
DCA/DCEC Code R802
1860 Wiehle Avenue
Reston, VA 22090
ARPANET: simmons@edn-vax.arpa
------------------------------
Date: Wed, 24 Jul 85 16:37:54 EDT
From: "Dr. Ron Green" (ARO) <green@BRL.ARPA>
Subject: Computer Science Taxonomy
I would like to find out if there is a generally accepted taxonomy
for computer science. The first level of break out that I desire
is hardware, software, and AI. I feel that I would
like to see two or three levels of detail below this. If there
are some taxonomies like this I would appreciate being told about
them. The next phase will be soliciting names of persons and their
categories of expertise for review of proposals for basic research.
Thanks,
Ron
[There are several such taxonomies. One of the best is the
Computing Reviews classification system (published in CACM,
January 1982). The various online abstracting services,
including those of the defense department, have their own
taxonomies, as do the librarians and, no doubt, the NSF and
various government statistical agencies. Academics in CS often build
taxonomies in support of curriculum development; see, for instance,
Schenk and Pinkert's survey in the 1978 National Computer Conference,
pp. 1209-1212. -- KIL]
------------------------------
Date: 24 Jul 85 10:15:27 EDT
From: Robert.Frederking@CMU-CS-CAD
Subject: AI databases?
[Forwarded from the CMU bboard by Laws@SRI-AI.]
I'm looking for a declarative knowledge-base to use as a domain for
the NL parser I'm working on. It must be frame-oriented and rich in domain
knowledge, and preferably should contain intentional information (what the
defining features of a particular subset are, for instance) and "common
sense" knowledge. (I don't actually expect to find all this in one KB.)
Note that I am specifically looking for content, not an empty KR system.
I'm already aware of the NLM database. Thanks.
------------------------------
Date: 24 Jul 85 09:47:46 EDT
From: Rob.Woodbury@CMU-CS-CAD
Subject: geometry survey
[Forwarded from the CMU bboard by Laws@SRI-AI.]
I am doing a survey on computer based representations of geometry in
engineering and architecture. The intent of the survey is to collect in one
place an overview of all (or as close as possible to all) existing modelling
techniques and applications and all current areas of research. Of particular
interest is any work on spatial reasoning, motion planning and vision
systems. I will make results available. Any pointers would be appreciated.
Thanks -rob-
------------------------------
Date: 21 Jul 1985 15:07:13-EDT
From: Bharat.Dave@CMU-CS-CAD
Subject: Re: Space Planning
Although this pertains to architecture, it would be interesting to hear
from others about issues of design and models of descriptions used.
Most of the work done in `space planning' in architecture, has concentrated
on geometric descriptions and manipulations (which is probably closer to
applications in robotics than architecture). Designers employ words, drawings
and perceptual notions which have not yet been fully investigated. To put
it differently, diagrams are used as a vehicle of statement as well as
interpretation of topological and semantic concepts.
To go beyond bin-packing spatial layouts, real world knowledge will have to
be built into the system (i.e. there are rules which are broadly observed,
some others come into play only in certain contexts; some of these are
stricter than the others and the rest are pure flights of fancy...).
Any of these rules or a combination of them, may be utilized for specifying
or evaluating given spatial configuration. And also, some mechanism for
alternating between various design-states will have to be built in.
Probably, what confuses the most about human designers is the kind of mental
representations they use. It seems more like abstract analog models of real
spaces and elements than simple surrogate verbal concepts.
`Mental Models' (ed.) by Gentner and Stevens has some interesting papers
on spatial models used by novices and experts in various domains.
--Bharat Dave
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Date: Sat, 20 Jul 85 14:40:28 edt
From: Tom Scott <scott%bgsu.csnet@csnet-relay.arpa>
Subject: ITP, how to order it
According to Ross Overbeek (overbeek@anl-mcs), who is one of the
developers of Argonne's Logic Machine Architecture/Interactive Theorem
Prover (LMA/ITP) and a co-author of "Automated Reasoning" (Wos et al.
1984), you can obtain the software from Numerical Algorithms Group (NAG)
at the following address and telephone number:
Numerical Algorithms Group
1101 31st Street, Suite 100
Downers Grove, IL 60515
(312) 971-2337
If I remember correctly, the cost of LMA/ITP was $75.00
(seventy-five). One of our logicians, Charlie Applebaum
(applebau@bgsu), is working on LMA/ITP with some of the people at Mitre
and Argonne, so that may be the reason for the low price charged to
BGSU. But I think the $75.00 price is what NAG charges anyone for
LMA/ITP, simply to cover the distribution costs. The same software is
available from one of the innumerable departments at Argonne National
Laboratory for something in the neighborhood of $1050.00 (one thousand
fifty). I always thought the federal government was expensive; now I
know it is.
Jai Guru Dev,
Tom Scott UUCP: cbosgd!osu-eddie!bgsuvax!scott
Dept. of Math. & Stat. CSNET/ARPANET: scott@bgsu
Bowling Green State Univ. ATT: 419-372-2636
Bowling Green OH 43403-0221
------------------------------
Date: Mon, 22 Jul 85 09:16 EDT
From: Scott Garren <garren@SCRC-STONY-BROOK.ARPA>
Subject: Symbolics LISP/PROLOG
From: Yigal Arens <ARENS@USC-ECLC.ARPA>
I'm interested in finding out about implementations of Prolog in Lisp or
Lisp in Prolog(?), or any other version of either that allows one to
program in both. [...]
Symbolics has a Prolog written in Lisp. The 3600 architecture has been
expanded with additional instructions that implement backtracking,
unification, and cut. We have also extended Lisp with a logic variable
data type. The result is a well integrated environment where the user
can call back and forth between the languages. All the operating system
and networking functions are accessible from Prolog. Symbolics Prolog
also offers what we believe is the highest performance of any
commercially available Prolog.
------------------------------
Date: 25 Jul 85 11:15:36 EDT
From: Tim <WEINRICH@RUTGERS.ARPA>
Subject: More Interlisp comments
Date: Mon, 8 Jul 85 09:50:16 edt
From: Eric Nyberg <ehn0%gte-labs.csnet@csnet-relay.arpa>
Subject: Re: Interlisp Comments
I disagree with Steven's conclusion that Interlisp "discourages"
comments. The *default environment* handles comments in a
discouraging way, but a few lines of code in the init file can remedy
the situation.
But all he said was that Interlisp "discourages" comments, not that it
prohibits them. The default Interlisp environment makes comments about as
inconvenient to use as it possibly can without actually prohibiting them.
Furthermore, as you yourself admit, the documentation which describes how to
change the environment is very difficult to find and use. And no matter how
you change the environment, you still have to be careful where you put your
comments. (The preferred place for documenting a variable would be right
where the variable is declared, which you can't do. My preferred place for
documenting a clause of a CONDition is at the beginning of the clause, which
you can't do. The nicest place to describe an argument which you're sending
to some function would be right after the argument itself, which you can't do.
Sometimes I like to include "afterthoughts" at the end of a function which
tell how that function might be improved or something, which you can't do.)
If this sort of thing does not "discourage" the use of comments, I
honestly don't know what it would take for a language to do so.
Twinerik
------------------------------
Date: Mon, 22 Jul 85 10:06 EDT
From: Jong@HIS-BILLERICA-MULTICS.ARPA
Subject: Re: Mistakes
The recent comment on "mistakes" in chess and the limitation of
expert systems to their (narrow) field of expertise brings up an
interesting point. Computer-science experts have been trying to
win chess championships for years; why aren't they trying to win
the World Series of Poker? The answer is simply that in poker,
you win or lose less on the basis of the cards in your hand and
more on the basis of the expression on your face and your
opponents'. The knowledge base for that game goes far beyond the
odds of filling an inside straight.
The great chess champion Emmanuel Lasker said that chess was
not simply a mathematical exercise but a fight, a fight between
two people. Lasker was a master of the psychological pressures
of the game. He knew when to make a deliberately inferior move
that rattled an opponent into thinking Lasker had a prepared
variation (one line of play exhaustively studied by one
opponent), when really Lasker had nothing planned but a head
game. Lasker knew which of his contemporaries to attack and
which to play defensively; which knew the openings well and which
were end-game masters; and which liked complications and which
shied away from them. With this knowledge he became champion.
A chess program is not likely to play based on its opponent,
because of the programming difficulties involved, and, I suspect,
because that is not an attractive line of research for its
programmers. Right now, though, human masters are beating chess
programs by playing to their weaknesses (for instance, when to
jump out of a book opening to the program's disadvantage). In a
larger sense, this is probably a discussion of "intuition" as it
applied to AI. Obviously, we have a long way to go before we
have an expert system that bases its conclusions based to any
degree on the fact that the inquiring human has grass on his
shoes.
[See Scientific American, July 1978, for an article on Nicholas
Findler's research into automating poker strategies. I seem to
recall that the project ended before a player was developed that
could detect and bluff the Mathematically Fair Player. -- KIL]
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End of AIList Digest
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