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AIList Digest Volume 2 Issue 051
AIList Digest Sunday, 22 Apr 1984 Volume 2 : Issue 51
Today's Topics:
AI Tools - Review of LISP Implementations,
Computational Linguistics - Stemming Algorithms & Survey,
Linguistics - Use of "and" & Schizophrenic Misuse of Metaphors,
Correction - Lovelace Encryption Seminar,
Seminars - Combining Logic and Functional Programming &
Learning Design Synthesis Expertise
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Date: 20 Apr 84 22:22:44 EST (Fri)
From: Wayne Stoffel <wes%umcp-cs.csnet@csnet-relay.arpa>
Subject: Review of LISP Implementations
Re: Bill Wong's article on three LISP implementations
He also wrote a series on AI languages that appeared in Microsystems. All
were 8-bit CP/M implementations.
August 1983, muLisp-80, SuperSoft Lisp, and Stiff Upper Lisp.
December 1983, XLISP, LISP/80, and TLC Lisp.
January 1984, micro-Prolog.
W.E. Stoffel
------------------------------
Date: Fri, 20 Apr 84 18:15 EST
From: Ed Fox <fox%vpi.csnet@csnet-relay.arpa>
Subject: Algorithms for word stemming and inverse stemming (generate
word)?
[Forwarded from the Arpanet-BBoards distributin by Laws@SRI-AI.]
Please send code, references, comments - about systems which can transform
words to stems and stems to words, in an efficient and effective fashion with
very small tables. There are a number of stemming algorithms, and some
systems that generate words from root+attribute_information. I would be
interested in a list of such, and especially of systems that do both in
an integrated fashion. Preferred are systems that can run under 4.x UNIX.
Many thanks, Ed Fox (fox.vpi@csnet-relay)
------------------------------
Date: Thu, 19 Apr 84 15:59:18 est
From: crane@harv-10 (Greg Crane)
Subject: foreign language dbases, linguistic analysis, for lang
word-proc
[Forwarded from the Arpanet-BBoards distribution by Laws@SRI-AI.]
Linguists, philologists, humanists etc. --
Are you using a computer for linguistic analysis? Access of
big foreign language data bases (Toronto Old English Dbase, or the
Thesaurus Linguae Graecae for example)? analysis or storage
of variant reading or versions? dictionary projects?
We have been doing a lot here, but nobody seems to have any
overall picture of what is being done round about. I would like to
find out and think its time those who are doing much the same thing
started talking. Any ideas on where a lot of work is being done and
how to facilitate communication?
Gregory Crane
Classics Department
Harvard University
------------------------------
Date: Fri 20 Apr 84 20:06:52-PST
From: Richard Treitel <TREITEL@SUMEX-AIM.ARPA>
Subject: Use of "and"
Come on, folks. When someone says "my brothers and sisters" they do not mean
the intersection of the two sets. Aside from its legal meaning of "or" which
I mentioned earlier, the English word "and" has at least two more meanings:
logical conjunction, and straight addition (which means union when applied to
sets). Though I'm willing to be contradicted, I believe that English usage
prefers to intersect predicates rather than sets. Namely, "tall and fat
people" can mean people who are both tall and fat (intersection), but "tall
people and fat people" means both the set of people who are tall and the set of
people who are fat (union).
- Richard
------------------------------
Date: 16 Apr 84 9:12:00-PST (Mon)
From: pur-ee!uiucdcs!marcel @ Ucb-Vax
Subject: Re: Use of "and"
Article-I.D.: uiucdcs.32300023
>>From watrose!japlaice
>> There are several philosophical problems with treating
>> `Indiana and Ohio' as a single entity.
>> The first is that the Fregean idea that the sense of a sentence
>> is based on the sense of its parts, which is thought valid by most
>> philosophers, no longer holds true.
>> The second is that ... `unicorn', `hairy unicorn', `small,
>> hairy unicorn' ... are all separate entities ...
On the contrary, the sense of "Indiana and Ohio" is still based on the senses
of "Indiana", "and" and "Ohio", if only we disambiguate "and". The ambiguity
of conjunction is well-known: the same word represents both a set operator and
a logical operator (among others). Which set operator? The formula
X in ({A} ANDset {B}) <= (X in {A}) ANDlog (X in {B})
allows ANDset to be either intersection or union. It is only our computational
bias that leads us to confuse the set with the logical operator. The formula
X in ({A} ANDset {B}) <=> (X in {A}) ANDlog (X in {B})
forces ANDset to be an intersector.
But we need only distinguish ANDset and ANDlog to preserve Fregean
compositionality; for that, it's immaterial which ANDset we adopt. In any
case, Bertrand Russell's 1908 theory of descriptions (as I read it) seems to
refute strict compositionality (words are meaningless in isolation -- they
acquire meaning in context).
Secondly, I don't recall Quine saying that `unicorn', `hairy unicorn', `small,
hairy unicorn' should all be indistinguishable. They may have the same referent
without having the same meaning.
Marcel Schoppers
U of Illinois @ Urbana-Champaign
{ ihnp4 | pur-ee } ! uiucdcs ! marcel
------------------------------
Date: 17 Apr 84 7:52:10-PST (Tue)
From: harpo!ulysses!gamma!pyuxww!pyuxss!aaw @ Ucb-Vax
Subject: Re: metaphors
Article-I.D.: pyuxss.311
[audi alteram partem]
For some interesting study on understanding of metaphors of the type you
refer to, look into Silvano Arieti (psychiatrist/NYU) work on
schizophrenic misuse of metaphors. It has some deep insights on the
relationship between metaphor and logic.
{harpo,houxm,ihnp4}!pyuxss!aaw
Aaron Werman
------------------------------
Date: 21 Apr 1984 17:00-PST
From: fc%USC-CSE@USC-ECL.ARPA
Subject: Lovelace Encryption Seminar
With regard to coded messages, I think natural stupidity has replaced
artificial intelligence in this regard. Fortunately, I have a
program to deal with walter's kind. So nobody has to run their
programs, here's an aproximate translation:
------------------------
The first computer programmer was a nineteenth century noblewoman,
Lad Augusta Ada Bron Lovelace, daughter of the poet Lord Bron.
As a teenager, Augusta displaed astonishing prowess in mathematics.
When she was eighteen augusta first saw Charles Babbage's analtical
engine, a calculating machine that was the forerunner of the modern
computer. In eighteen fortytwo, she translated a paper on the
engine from French to Knglish adding her own voluminous notes. In
subse:uent writings she described the "loop" and "subroutine"
concepts a centur before their implementation in electronic
digital computers .but as far as I know, however, she never did
anthing with encrption/. Lad Lovelace and Babbage had a long
and close friendship and she was a dedicated partner in his work
with the analtical engine. Unfortunatel she was held back b
antiyfeminist attitudes and b her own obsession with gambling on
horse races. Lad Lovelace died of cancer at age thirtysix. Now
that ouve decoded this message, let's all get back to work.
---------------------------
Please, Walter, next time you want to get the message out:
#@(& $%& $#(& (^$% ^&(#$&%! (& %($( (* ^&*(*% &%& @&&#&& $#&$&%!
Fred
[The responsibility for forwarding the previous message, and this one,
to the AIList readership rests with me. -- KIL, AIList-Request@SRI-AI.]
------------------------------
Date: Wed 18 Apr 84 14:13:31-PST
From: SHORT%hp-labs.csnet@csnet-relay.arpa
Subject: Seminar - Combining Logic and Functional Programming
[Forwarded from the SRI-AI bboard by Laws@SRI-AI.]
JOSEPH A. GOGUEN
SRI International
COMBINING LOGIC AND FUNCTIONAL PROGRAMMING -- WITH EQUALITY, TYPES, MODULES
AND GENERICS TOO!
Hewlett Packard Computer Colloquium - April 26, 1984
This joint work with J. Meseguer shows how to extend the paradigm of logic
programming with some features that are prominent in current programming
methodology, without sacrificing logical rigor or efficient implementation.
The first and most important of these features is functional programming;
full logical equality provides an elegant way to combine the power of Prolog
(with its logical variables, pattern matching and automatic backtracking)
with that of functional programming (supporting functions and their
composition, as well as strong typing and user definable abstract data types).
An interesting new feature that emerges here is a complete algorithm for
solving equations that contain logical variables; this algorithm uses
"narrowing", a technique from the theory of rewrite rules. The underlying
logical system here is many-sorted Horn clause logic with equality. A
useful refinement is "subsorts", which can be seen as an ordering relation
on the set of sorts (usually called "types") of data. Finally, we provide
generic modules by using methods developed in the specification language
Clear. These features are all embedded in a language call Eqlog; we
illustrate them with a program for the well-known Missionaries and Cannibals
problem.
Thursday, April 26, 1984 4:00 p.m.
Hewlett Packard Laboratories
Computer Research Center
1501 Page Mill Road
Palo Alto, CA 94304
5M Conference Room
------------------------------
Date: 19 Apr 84 13:28:14 EST
From: Michael Sims <MSIMS@RUTGERS.ARPA>
Subject: Seminar - Learning Design Synthesis Expertise
[Forwarded from the Rutgers bboard by Laws@SRI-AI.]
Learning Design Synthesis Expertise by Harmonizing Behaviors with
Specifications
Speaker: Masanobu Watanabe <Watanabe@Rutgers.Arpa>
NEC Corporation, Tokyo, Japan
Visiting Researcher, Rutgers University
Series: Machine Learning Brown Bag Seminar
Date: Wednesday, April 25, 1984, 12:00-1:30
Location: Hill Center, Room 254
VEXED is an expert system which supports interactive circuit design.
VEXED provides suggestions regarding alternative implementations of
circuit modules, as well as warnings regarding conflicting constraints.
The interactions between a human designer and the system give
opportunities for the system to learn expertise in design synthesis by
monitoring the human designer's response to advice offered by the
system. From this point of view, there are two interesting cases. One
occurs when the designer ignores the advice of the system. Another
occurs when the system cannot provide any advice but the human designer
can continue his own design.
The system has to learn as many things as possible by analyzing a
single precious example, because it is difficult for the system to
obtain many examples from which to form a particular concept. The
problem space in the module decomposition process can be viewed as one
with both states consisting of a set of modules and operators, which
will be called implementation rules. This talk discusses the
implementation rule acquisition task which is intended to formulate an
implementation rule at an appropriate level of generality by monitoring
a designer's circuit implementation. This task is to learn
implementation rules (a kind of operator, but not quite like LEX's
operators), while LEX's task is to learn heuristics which serve to
guide useful operators.
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End of AIList Digest
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