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AIList Digest Volume 5 Issue 054
AIList Digest Tuesday, 24 Feb 1987 Volume 5 : Issue 54
Today's Topics:
Administrivia - Problem with Issue 51,
Queries - Financial Expert Systems & Real-Time AI &
Recognition of Text Written by Hand & Automatic Theorem Proving &
Network Complexity & DBMS Issues in KBs
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Date: Mon 23 Feb 87 10:46:16-PST
From: Ken Laws <Laws@SRI-STRIPE.ARPA>
Reply-to: AIList-Request@SRI-AI.ARPA
Subject: Problem with Issue 51
Some of you may have found only a single message in Volume 5, No. 51,
the analysis of Artificial Intelligence citations (by Lawrence Leff).
That issue also contained a discussion by John McCarthy on taking
a "design stance" towards the cognition problem and a review of a
review of Minsky's new book.
Unfortunately, the first message ended with a line containing a single
period. This is take as an end-of-message flag by some mailers, and
so the second and third messages were lost or hidden.
If you need a remailing of the issue, with the offending line removed,
just send a request to AIList-Request@SRI-STRIPE.ARPA.
-- Ken Laws
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Date: Mon 23 Feb 87 09:28:41-PST
From: Frances Borison <BORISON@SRI-KL.ARPA>
Subject: Financial Expert Systems
Does anyone know of any financial expert systems that are commercially
available for purchase and that run on either general purpose computers or AI
workstations? I am aware of Planpower by Applied Expert Systems
(APEX) and Financial Advisor by Palladian Software. Any assistance
would be appreciated.
Frances Borison.
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Date: 23 Feb 87 18:35:44 GMT
From: teknowledge-vaxc!rburns@SRI-UNIX.ARPA (Randy Burns)
Subject: Wanted speaker familiar with financial applications of AI
A friend of mine is involved with an IEEE group which is sponsoring a
seminar on financial applications of Artificial Intelligence. I would
appreciate anyone with experience in this area to contact me so I can
forward your name to him.
Randy Burns
Teknowledge Inc.
415-424-0500 x543
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Date: 17 Feb 87 12:26:52 GMT
From: mcvax!ukc!tcom!idec!camcon!ijd@seismo.css.gov (Ian Dickinson)
Subject: Research in Real-Time A.I.
I'm currently engaged in a small research project looking at the problems
of updating AI databases in real time. [By database, I mean that collection
of information that I am currently reasoning against - not the large
commercial variety.]
A typical problem in the domain is that you have N (where large(N)) sensors
attached to a process plant all throwing lots of data with low information
content at an intelligent fault diagnosis system. The system has to cope
with contradictory data, have good coverage of the incoming signals, but
still be able to respond quickly to high-priority situations.
The particular issues that I am concerned with are:
(1) what are the representational inadequacies of current AI notations
that are suited to doing real time problems and/or handling noisy and
contradictory data?
(2) what are the computational costs of using such notations?
Primary choices for handling mucky, changing data are the RMS family
(Doyle, de Kleer etc) and other non-monotonic logics, so these are typical
of the notations that I am referring to. So the issues become: what can't
you do with them, and what would it cost anyway?
The questions I would like to submit to net.land are:
o anybody doing any work on extending non-monotonic notations in wierd
directions (eg integrating them with uncertain inference techniques)?
o anybody got any pet real-time AI problems?
o anyone else working in the real-time field?
Please mail responses directly to me, and I will post a summary for
discussion later.
Thanks in advance,
Ian.
--
!! Ian Dickinson Cambridge Consultants Ltd, AI group !!
!! Voice: (0223) 358855 [U.K.] Email: ijd%camcon.co.uk !!
!! uucp: ...!seismo!mcvax!ukc!camcon!ijd or: ijd%camcon.uucp !!
>> Disclaimer: All opinions expressed are my own (surprise!). <<
------------------------------
Date: Thu, 19 Feb 87 22:45:18 +0100
From: Hakon Styri <styri%vax.runit.unit.uninett@NTA-VAX.ARPA>
Subject: Recognition of text written by hand
Is there anybody with knowledge about work going on in the field of
machine recognition of text written by hand. I'm not interested in
"understanding" the text, just converting it into machine readable
form. And, the text is already written so special pen and paper is
no good.
------------------------------
Date: 20 Feb 87 04:32:09 GMT
From: cartan!brahms.Berkeley.EDU!cotner@ucbvax.Berkeley.EDU (Carl
Cotner)
Subject: automatic theorem proving
Can anyone on the net recommend any books or articles about
automatic theorem proving? I am interested (I think) in the subject,
but know almost anything about it. Any reference would be very
welcomed. Thanks.
ucbvax!brahms!cotner Carl Cotner/UCB Math Dept/Berkeley CA 94720
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Date: 19 Feb 87 22:47:52 GMT
From: ihnp4!ihnp3!mth@ucbvax.Berkeley.EDU (Mark Horbal)
Subject: Network Complexity
(sorry if this is a duplicate posting, but my machine burped)
I am in the process of putting together a paper which attempts to
motivate planning and development of software based Network Management tools.
In general, such tools would be both STRATEGIC, eg. network topology planning,
from the perspective of capacity, security, fault tolerance, etc, and
TACTICAL, such as visualization of network activity, dynamic routing, fault
recovery, congestion avoidance, etc. Clearly, this fields is ready for
and in desperate need of AI, which is why I'm addressing it to this group.
Now, my intuition tells me that as these networks become more complicated,
we'll realize that the seat-of-the-pants network management we're used to is
inadequate, and we'll wish that we had spent time developing the right tools
to do the job. I envision the complexity of our computer networks to be
exploding at some exponential rate, while our ability to understand and
control them is falling behind, growing relatively slowly. This brings
me to my QUESTION:
If we define the "complexity" of a computer network as a
measure of difficulty in observing, understanding, and
excercising a modicum of control over it, how is this
"complexity" estimated?
If we further choose a simple but intuitive way of representing
a computer network by a graph, how do we quantify this "complexity"
with respect to the graph's topology?
Clearly metrics such as the number of nodes, edges circuits etc have intuitive
appeal, but do not individually seem to convey the underlying combinatorial
explosion that, I believe, lurks underneath.
Are you aware of any analytic, graph-theoretical, heuristic, empirical,
or otherwise useful metrics of such "complexity"? I am not necessarily
looking for some absolute measure of the thing, but general concepts.
Any facts, comments, opinions and thoughts will be most appreciated.
M. Horbal
@ Bell Labs
ihnp4!ihnp3!mth
(312) 979-6496
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Date: Mon, 23 Feb 87 13:01:35 EST
From: tim@linc.cis.upenn.edu (Tim Finin)
Subject: DBMS issues in KBs
A colleague is interested in what work has been done involving the
traditional concerns of a DBMS for Knowledge Bases (e.g. concurrency,
security, query optimization, etc). I don't think that these issues
have been addressed in any systematic way. Can anyone offer any
references to work regarding such things?
From: Susan Davidson <Susan@cis.upenn.edu>
Date: Thu, 19 Feb 87 15:00 EST
Can you point me to any papers that speak to the exact problems of updating,
concurrency, optmization, etc. in knowledge bases?
sbd
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End of AIList Digest
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