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AIList Digest Volume 3 Issue 110
AIList Digest Thursday, 15 Aug 1985 Volume 3 : Issue 110
Today's Topics:
Queries- Master Bibliography & OPS5 for Symbolics,
Bindings - Friedman & Johnson,
AI Tools - IBM Prolog and Expert Systems Development,
Logic Programming - Opinion,
Expert Systems - Definition & Database Systems & Rule Induction
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Date: Tue 13 Aug 85 09:28:58-PDT
From: Mike Dante <DANTE@EDWARDS-2060.ARPA>
Subject: Master Bibliography
I suspect that I am not the only one reading this BB who finds some
of the submissions less than completely understandable due to lacunae in my
own background. Hence a suggestion: Would it make sense to establish and
maintain a bibliography (hopefully annotated), whose existence and address
would be mentioned in the header of the AIList Digest? Then when someone
like myself wanted to understand more, he or she could FTP a copy of the
bibliography and with a little study, at least understand the terminology.
------------------------------
Date: Wed, 14 Aug 85 07:59:12 edt
From: Martin Lee Schoffstall
<schoff%rpics-zen%rpi.csnet@csnet-relay.arpa>
Subject: ops5 for symbolics
does anyone have any pointers to an OPS5 for the symbolics3600?
thanks,
marty schoffstall
schoff%rpics.csnet@csnet-relay ARPA
schoff@rpics CSNET
seismo!rpics!schoff UUCP
martin_schoffstall@TROY.NY.USA.NA.EARTH.SOL UNIVERSENET
RPI
Computer Science Department
Troy, NY 12180
(518) 271-2654
------------------------------
Date: Tue, 13 Aug 85 15:28:07 cdt
From: Raj Doshi <doshi%umn.csnet@csnet-relay.arpa>
Subject: want address of JPL...
Hi, would anyone know the address of
a Dr. LEN FRIEDMAN who used to (or still is) with
(JPL) Jet Propulsion Laboratory ??
I have the old address. I sent a letter, but it was returned to me
by U.S.Mail authorities.
I know for sure that this was his address in June 1983.
The old address was : Dr. Len Friedman
=========== Automated Problem Solving
Jet Propulsion Laboratory
California Institute Of Technology
4800 Oak Grove Drive
SUITE # 278
Pasedena, CA 91109
Would anyone know his PHONE-Number ?????
Would anyone know his new address (surface or email) ??
Thanks very very much in advance. Please respond directly to me.
Thanks again.
--- raj doshi, University of Minnesota
doshi%umn.csnet@csnet-relay.arpa
------------------------------
Date: 13 Aug 1985 0855-PDT (Tuesday)
From: Johnson@ISI-VAXA
Subject: binding and request
I am told that a request for my current address appeared on ailist
recently. My arpanet address is johnson@isi-vaxa; my mailing address is
W. Lewis Johnson
USC / Information Sciences Institute
4676 Admiralty Way
Marina del Rey, CA 90292-6695
Also, could you please add my name to the recipients of ailist? Thanks.
Lewis
------------------------------
Date: Sun, 11 Aug 85 10:22 P
From: Henry Nussbacher <vshank%weizmann.BITNET@WISCVM.ARPA>
Subject: IBM announces Prolog and Expert Systems Development
VM Programming in Logic 5785-ABH One Time Charge Lang: Assem, REXX
"VM Programming in Logic is an IBM implementation of the PROLOG programming
language. It is suited for the research and development of applications in
artificial intelligence including: expert systems, automated deduction,..."
"VM Programming in Logic provides the following features:
- Debugging Facilities
- Communication with VM/SP ..., SQL/DS ..., and LISP/VM... (Note: the
use of SQL/DS and LISP/VM are optional.)"
The Availability is Sept. 6, 1985.
Documentation: PDOM SH20-6541
Expert System Consultation Environment/VM 5798-RWP OTC or Monthly
Expert System Development Environment/VM 5798-RWQ OTC or Monthly
Language: PASCAL/VS
"These two complementary program offerings provide the facilities
for developing and executing expert systems. Expert System
Development Environment/VM is used to 'build' knowledge bases. Expert
System Consultation Env./VM is used to 'consult' those knowledge
bases. ..."
"These program offerings provide the following features:
- English-like rules
- Specialized editors with automatic checking to facilitate the entry and
modification of knowledge base objects.
- Explanation during consultation: 'Why?' provides a logical explanation
for a certain request; 'What?' provides a more detailed explanation of
the question being asked.
- Debugging support.
- Two inference processes: forward chaining, backward chainging.
- Online help."
"The Expert System Development Environment/VM requires the Expert System
Consultation Environment/VM. Once the knowledge base (set of rules) has been
developed, it can be replicated and used by the Expert System Consultation
Environment/VM without the presence of the Expert System Development Env./VM."
Availability: Sept. 6, 1985
Documentation: Gen. Info. Man. GH20-9597, ESDE Install: SH20-9607,
ESDE User Guide SH20-9608, ESDE Ref. Man. SH20-9609.
ESCE Install: SH20-9605, ESCE User Guide SH20-9606.
These are supported out of Irving Texas. From Announcement Letter 285-284,
August 6, 1985.
------------------------------
Date: Wed, 14 Aug 85 00:40:17 EDT
From: Carl E. Hewitt <HEWITT@MIT-MC.ARPA>
Subject: Prolog will fail as the foundation for AI; so will LOGIC as
a PROGRAMMING Language
Prolog (like APL before it) will fail as the foundation for Artificial
Intelligence because of competition with Lisp. There are commercially
viable Prolog implementations written in Lisp but not conversely.
LOGIC as a PROGRAMMING Language will fail as the foundation for AI because:
1. Logical inference cannot be used to infer the decisions that need to be
taken in open systems because the decisions are not determined by
system inputs.
2. Logic does not cope well with the contradictory knowledge bases inherent
in open systems. It leaves out counterarguments and debate.
3. Taking action does not fit within the logic paradigm.
[Carl also sent this message to the philosophy of science mailing
list (Phil-Sci-Request%MIT-OZ@MIT-MC), and it has triggered several
responses about Prolog/Logic Programming/AI. I am happy to let
Phil-Sci carry the discussion, although it could just as easily
have fit within AIList or the Prolog digest. For a good elaboration
of Carl's thesis on open systems (networks, banking systems,
nondeterministic distributed systems, etc.), see his article in
the April '85 issue of BYTE. It's interesting reading, as are most
of the articles in this special issue on AI. (The April Fool's
What's Not column on pp. 96-97 is fun too.) -- KIL]
------------------------------
Date: Mon, 12 Aug 85 10:07 P
From: Henry Nussbacher <vshank%weizmann.BITNET@WISCVM.ARPA>
Subject: Expert System definition vs Database Systems
I have been reading over the definitions of what an expert system is and
isn't and I have seen in many of the comments that an expert system needs
to be able to learn as it continues. Somehow, I have always felt Expert
Systems to be glorified database systems. A database system gains more
information as you add data to it. Th common example of Expert Systems
(in my opinion) is the DOCTOR program:
1) Does the patient have a fever? Y
2) Has the patient vomitted in the past 24 hours? Y
3) Are the pupils dilated? N
4) etc...
The AI program asks questions and based on the answers, determines what
future questions to ask. In the end it narrows it down and comes up with
a diagnoses based on the results of the questions.
But I know of many database packages where a question in the form of:
FIND FEVER > 100 & VOMIT = YES & DILATED = NO
DISPLAY ALL
My question is: What distinguishes the database search and display interface
from an AI Expert System?
Hank
------------------------------
Date: Fri 9 Aug 85 18:27:09-EDT
From: SRIDHARAN@BBNG.ARPA
Subject: Rule Induction and Expert Systems
Masinter narrows it too far, making it anthropocentric.
During the Machine Learning workshop at Allerton, IL, I heard Don Michie
talk about the efforts of one of his friends. This effort involved building
an ES to analyze EKG charts. They built two systems, one pretty closely
following the Expert System methodology that Larry talked about. The other
system was constructed by using a rule-induction technique, giving it
a set of input charts and their analyses. The induction technique was
biased toward a set of useful features for rule formation. The comparison
of the two systems, yielded the conclusion that the induced-rule set
outperformed the other in terms of both speed of execution and quality of
results.
One might admit so called expertise may be included in such weak forms
as the bias given to the induction technique. Nature provides constraints
for scientific theories. Some of us would like to tap into this ultimate
source of "expertise" rather than stick to the derived expertise of humans.
Masinter's description could be broadened to include this, if each
occurrence of "expert" is not necessarily viewed as a human expert.
P.S. Note that with the induced rule-set the system might be capable of
explaining the rules themselves, by refering back to the cases.
Another case serves as reference example. Larry and I both particpated in
the Dendral and Meta-Dendral efforts at Stanford. The latter effort was
aimed at rule formation for a class organic molecules; rules to characterize
how bonds break in a mass spectrometer. Validated rules for several class
of molecules were formed and incorporated into Dendral. Here both
nature and human experts participated, but the human experts did not
construct the rules.
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End of AIList Digest
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