HDTenEightyP/NetNews huggingface dataset:
From: weber@charlie.iam.unibe.ch (Stephan Weber)
Subject: Network Design Algorithms and AI Technology
Reply-To: weber@iam.unibe.ch  
Organization: Dept. of Computer Science, University of Berne, Switzerland
Date: Thu, 19 Nov 1992 15:46:23 GMT


Hello

Help for Network Design Algorithms and AI Technology!!!!

I am working on a project to design telecomunication networks. I found in the 
book "Data Networks " by Dimitri Bertsekas and Robert Gallagher (1987) the
description of the Capacity Assignment Problem. There are a formal Description
and a heuristic algorithm given.

Now I have a question. Do you know other papers or books which describe this
kind of problems (Design of Backbone - Network based on traffic matrices).
Also I would like to get in concact with people working in thies area to discuss
problems and questions.

My interests are specially in people working with operation research methods
and on the other side with artificial intelligence methods. My question is, 
how these two techniques can be used to design in a efficient way cost-effective
telecommunication networks.

I enjoy all the information you can provide me. Thanks a lot.

Stephan 

*********************************************************
* Stephan Weber                                         *
* Institut fuer Informatik und angewandte Mathematik    *
* Universitaet Bern                                     *
* Laenggassstrasse 51                                   *
* CH - 3012 Bern                                        *
* Telephon:	..41 31 65 49 03                        *
* TeleFax	..41 31 65 39 65                        *
* eMail		weber@iam.unibe.ch                      *  
*********************************************************

Keywords:
From: lou@cs.rutgers.edu (Lou Steinberg)
Newsgroups: comp.ai
Subject: Re: How to pick a grad school [excerpt from Stephen Gould]
Date: 17 Nov 92 20:40:02 GMT
	<1992Nov16.171722.23489@CSD-NewsHost.Stanford.EDU>
	<1992Nov16.211341.7784@ennews.eas.asu.edu>
Reply-To: lou@cs.rutgers.edu
Organization: Computer Science Dept., Rutgers University, New Brunswick, NJ
	08903
In-reply-to: rao@parikalpik.eas.asu.edu's message of 16 Nov 92 21:13:41 GMT

The recent posts on choosing a grad school have been very good, and pretty
much right on the money from my experience both as a student and as a faculty
member, with one exception:

In my experience (meaning Stanford some (too many :-) years ago and
Rutgers since then), you are not really choosing an advisor when you
choose a school.  Rather, you are choosing a small pool from which
your advisor will be drawn.  There have been several cases at Rutgers
where students began working with one advisor, found they could not
get along with him (or he with them), and switched to another.
Students have switched from me to my colleagues and from my colleagues
to me.  In many cases, students who almost certainly would not have
finished had they not switched have gone on to do theses ranging from
creditable to excellent.  In fact, thinking about specific cases, I can
think of more where this has happened than where it has not.

This argues for choosing a school with several faculty members you
think you might work with.  It also argues for being flexible about
thesis topic and, to some extent, area.  After all, what are the
chances that 15 years from now you will be working on the same narrow
area as your thesis?  (It has been common in my experience that a
student doesn't even get through a *thesis*, let alone a career,
without some substantial change in focus.)
--
					Lou Steinberg

uucp:   {pretty much any major site}!rutgers!aramis.rutgers.edu!lou 
internet:   lou@cs.rutgers.edu
From: srt@aero.org (Scott R. Turner)
Newsgroups: comp.ai
Subject: Re: Mechanization of creativity
Date: 23 Nov 92 23:12:39 GMT
Organization: The Aerospace Corporation, El Segundo, CA
NNTP-Posting-Host: sun-marino.aero.org

tolman%asylum.cs.utah.edu@cs.utah.edu (Kenneth Tolman) writes:
>  I am looking for references on papers specifically on mechanized 
>creativity.  Where might I find such?

Lenat, Douglas B., ``AM: An Artificial Intelligence Approach to
Discovery in Mathematics as Heuristic Search'', Stanford AI Lab, Memo
AIM-286 (Ph.D. Dissertation), Stanford University, Dept. of Computer
Science, 1976.

Mueller, E. T. \fIDAYDREAMER...\fR. (Ph.D. Dissertation) Artificial
Intelligence Laboratory, Computer Science Department, University of
California, Los Angeles, 1987.

Turner, Scott R., ``A Case-Based Model of Creativity'', Proceedings of
the Thirteenth Annual Conference of the Cognitive Science Society,
Chicago, 1991.

Turner, Scott R., ``MINSTREL: A Computer Model of Creativity and
Storytelling'' (Ph.D. Dissertation) Artificial Intelligence
Laboratory, Computer Science Department, University of California, Los
Angeles, December, 1992.

The other good references are the notes from the workshops on
creativity at AAAI-91 and IJCAI-91.  Unfortunately, these notes aren't
published, and in the case of IJCAI-91 are only abstracts.

There will be a creativity symposium at the AAAI Spring Symposiums next
spring.

					-- Scott T.
Xref: sparky comp.ai:4350 news.groups:22519
Newsgroups: comp.ai,news.groups
Subject: Re: RFD -- where to put "fuzzy"?
From: tanaka@til.til.com (Yokichi Tanaka)
Date: Thu, 19 Nov 1992 21:44:01 GMT
Organization: Togai InfraLogic, Inc.

In article <1992Nov18.041604.8072@sol.ctr.columbia.edu>, jwiegand@moe.eng.temple.edu () writes:
|> Sci.logic.fuzzy sounds good!
|> jim jwiegand@moe.eng.temple.edu

It sounds like most people want a fuzzy newsgroup in 
"sci.logic.fuzzy".  It sounds good to me, too.

By the way, since fuzzy is a relatively new field, my hope is that
the newsgroup will be a place where we can share, teach and help 
each other in a constructive and amicable manner.  (And, I'm
confident that's how it'll end up.)

Just a few more weeks, everyone.

-- 
Yoke (Yokichi) Tanaka      Togai InfraLogic, Inc.    "fuzzy"
tanaka@til.com             Irvine, California, USA
                           714-975-8522
In case you're wondering ... I am male.
Xref: sparky comp.ai:4375 news.groups:22741
From: emily@azariah.tamu.edu (Emily Glass)
Newsgroups: comp.ai,news.groups
Subject: Re: RFD -- where to put "fuzzy"?
Date: 23 Nov 92 14:48:41 GMT
Organization: Texas A&M University, Dept. of Electrical Engineering
NNTP-Posting-Host: azariah.tamu.edu

In article <1992Nov21.051518.27956@kong.gsfc.nasa.gov> joslyn@kong.gsfc.nasa.gov (Cliff Joslyn) writes:
>
>Putting "fuzzy" under comp.ai is like putting "differential equations"
>under sci.engr.civil. 
>
.
.
.

>To be technically accurate, it should be sci.math.information.fuzzy,
>which is cumbersome, and requires the creation of sci.math.information
>(for the MOST general case). sci.math.fuzzy is acceptible, so is
>sci.fuzzy.
>
>Neither comp.fuzzy nor sci.engr.fuzzy are an especially good idea (who
>would put CLASSICAL information theory under comp or engr?), but I
>guess I could live with them. But comp.ai.fuzzy is just silly.
>

If sci.engr.fuzzy excludes classical information theory side of fuzzy
logic, then sci.math.fuzzy excludes the applied control side of fuzzy
control.

I definitely *don't* like sci.math.fuzzy.  As you pointed out fuzzy 
logic/control encompasses many areas: math, information sciences, 
control, engineering, computer applications, and possibly even
artificial intelligence.  

With all this said, I now am beginning to favor sci.fuzzy.  I still like
sci.logic.fuzzy better thatn sci.math.fuzzy.

Emily
From: manent@titan.ksc.nasa.gov
Newsgroups: comp.ai
Subject: NEED INFO ON IMAGE ENHANCEMENT
Date: 23 Nov 92 13:55:24 EST
Organization: NASA, Kennedy Space Center

PLEASE, I NEED INFORMATION OR SOURCES OF INFORMATION ON IMAGE ENHANCEMENT.
IF YOU HAVE ANY INFO, PLEASE SEND ME A MESSAGE AT:

MANENT@TITAN.KSC.NASA.GOV
OR
59228581V@SERVAX.FIU.EDU

THANKS,
DIANA MANENT
Newsgroups: comp.ai
From: shrdlu@willow.sdd.trw.com (Lynda L. True)
Subject: Re: Grad school comments
Organization: TRW Inc., Redondo Beach, CA
Date: Tue, 17 Nov 92 16:03:48 GMT

In article <1992Nov16.191814.10733@rchland.ibm.com> bechdol@vnet.ibm.com writes:
>In article <1992Nov16.150247.3613@aisb.ed.ac.uk>, reiter@aisb.ed.ac.uk writes:

>|> 6) Most important of all.  Are you sure you really, *really*, want to go
>|> to grad school?  A lot of people drift into a Ph.D program because its
>|> expected of them by their parents, undergrad professors, etc., or simply
>|> because its the course of least resistance (puts off that horrible process
>|> of actually having to find a job in the real world).  But an academic
>|> career is *not* for everyone, and there are a lot of other options
>|> available, especially for the computer-literate.  Be sure that *you* are
>|> the one who wants to go to grad school, not your parents or your undergrad
>|> mentor.

>In general, I would agree.  However, if you intend to pursue an AI career in
>industry, then you better be prepared to show your M.S. or Ph.D.  Much in the
>same way you have to have a High School Diploma or a B.S., a graduate degree is
>pretty much required as proof of competency in the field of AI.

Hah! Again I say HAH! I've been working in the field of AI for ten (count 'em,
ten) years, and I have a BA. Not even a BS, and not even in comp sci (although
I DID minor in comp sci).

>Bottom line: If you want to pursue a career in AI, then get the graduate degree
>(even if you don't want to)... get it done... it's a "union" card.

Nope. It's not only NOT a union card, but out of the productive people I've
worked with, only one has had a doctorate (which was in psych), and a small
handful have had master's degrees. Advanced degrees are for those who are
serious about research. If you can't make it in research, don't think that
industry wants you.

>Added dislaimer: Of course, it is possible to have a career in AI without a
>graduate degree, but it's just not very probable.

Yeah, right. In the past ten years, I've worked with lots and lots of people.
They didn't have graduate degrees for the most part, and they have had great
careers. In fact, the only person that I've known who has an AI background and
is also out of work has a doctorate.

Think about it. PhD => Research or Teaching... Not $$$$$$$$

Lynda
-- 

shrdlu@rowan.sdd.trw.com (Lynda L. True)
Work Phone - (310) 812-1660 or (310) 812-1570
From: corey@amiganet.chi.il.us (Corey Sweeney)
Newsgroups: comp.ai
Subject: faq
Date: 16 Nov 92 01:25:06 GMT
Organization: Amiga Network Information Systems

Would somebody please send me a FAQ for this newsgroup?  thanks

Corey

--------------------------------------------------------------------
Corey Sweeney
corey@amiganet.chi.il.us
I do not own a amiga!
Newsgroups: comp.ai,comp.ai.edu,sci.cognitive
From: stas@netcom.com (Stanislav Malyshev)
Subject: Re: B.S. Degree
Organization: Netcom - Online Communication Services (408 241-9760 guest)
Date: Mon, 23 Nov 1992 02:23:41 GMT

In article <1992Nov22.031734.945@linus.mitre.org> crawford@boole.mitre.org (Randy Crawford) writes:
>
>True, if you're fond of hardware.  But the better preparation for advanced 
>work in CS is a bachelor's degree in math.  And a BS in marketing with a MS 
>in CS is a very good combination (or a BS in CS followed by a MBA).  Just 
>about _any_ technical or business degree followed by the MS in CS is a healthy
>combination.  Just ask an ex-zoologist such as myself.
>
>| Randy Crawford        crawford@mitre.org        The MITRE Corporation
>

Well, that depends.  If the "advanced work in CS" is hardware-related,
say MPP, then EE would probably be better than math.

And one doesn't see much math in areas like AI, eh?  Unless one is doing
meta-theorem-prover stuff, or some other remnant from the good old days
of there-is-an-algorithm-and-a-stupid-formalism-for-everything.

-S
-- 

-------------------------------------------------------------------------------
Stan Malyshev		|    Open up the windows and let the fresh air out,
stas@soda.berkeley.edu	|    said the television to the shackled children..
stas@netcom.com		|		- King Missile
-------------------------------------------------------------------------------

Newsgroups: comp.ai
From: fb42@rummelplatz.uni-mannheim.de (Wolfgang Eger)
Subject: Utrecht University internal paper
Date: Mon, 16 Nov 92 22:35:30 GMT
Organization: RUM
X-Newsreader: Tin 1.1 PL4

Hi,

I'm looking for following reference:

Pascal J.F. de Vink, "On Integration of Neural Networks and Expert Systems",
Utrecht University internal paper, January 1991


If anybody knows about this paper or has a copy from it, please contact me
or send me the paper via E-Mail

Wolfgang Eger
fb42@rummelplatz.uni-mannheim.de


Carl-Zuckmayer-Str. 14/63
6800 Mannheim
W-Germany

Phone: Germany 0621/303745

Newsgroups: comp.ai
From: moshier@world.std.com (Stephen L Moshier)
Subject: Re: Looking for Good Intro to Bayesian Classifiers
Organization: The World Public Access UNIX, Brookline, MA
Distribution: usa
Date: Sat, 21 Nov 1992 00:22:41 GMT

  The three-volume set by Van Trees includes a good introduction to
this subject.  Its title is something like _Detection, Estimation,
and Modulation_.

Newsgroups: comp.ai
From: ginsberg@t.Stanford.EDU (Matthew L. Ginsberg)
Subject: Re: How to pick a grad school
Organization: Computer Science Department, Stanford University.
Date: Mon, 16 Nov 1992 17:17:22 GMT

In article <srt.721931824@sun-marino> srt@aero.org (Scott R. Turner) 
provides some excellent adice about picking a grad school.  One thing
he advises (and I agree) is to talk to the senior students where you're
thinking about going.

This is *definitely* good advice, but take what they say with a grain
of salt -- they've had a very lopsided view of graduate school (since
they've got a sample size of 1 in most cases), and it is often not
clear even to senior students how good an education they're getting.
But they certainly *will* have important things to say about support,
faculty availability and so on.

Mr. Turner also says:

>  If it comes down to picking
>between an advisor with a lesser reputation but better interpersonal
>and teaching skills, or an advisor with a better reputation but poor
>interactions with his graduate students, I advise choosing the former.
>You can always put the latter on your committee and get whatever
>inputs from him you need, but if you make him your advisor you may end
>up suffering needlessly because of his poor teaching skills.

I think I disagree here.  Committee members simply don't have the
level of technical input that your faculty advisor will.  Yes,
graduate school will teach you (hopefully) to organize your time,
teach, write papers and present them.  But those are all things that
you can, if need be, learn elsewhere (albeit perhaps with some
difficulty).  What graduate school teaches you that you can't learn
anywhere else is to be a scientist.  And the person you learn that
from, more than anyone else, is your faculty advisor.

Of course, this isn't to say that an advisor has no responsibilities
in these other areas.  But if the single irreplaceable thing you will
learn from your advisor is to be a scientist, you should -- probably --
select him more on that basis than on others.

						Matt Ginsberg

Xref: sparky comp.ai:4293 sci.math.symbolic:2977
From: hrubin@pop.stat.purdue.edu (Herman Rubin)
Subject: Re: Looking for Good Intro to Bayesian Classifiers
Organization: Purdue University Statistics Department
Distribution: usa
Date: Tue, 17 Nov 1992 18:03:27 GMT

In article <19293@ucdavis.ucdavis.edu> f175003@wilma.ucdavis.edu writes:
>I am looking for a book or paper with a good introduction into using 
>Bayesian Classifiers preferably with a few examples showing how to 
>determine the probabilities.  I understand the idea behind a Bayesian 
>Classifier, but I have looked at a couple of examples of Bayesian 
>Classifiers and they appeared to use maximum likelihood estimators to 
>determine the values for the various probabilities.  According to my 
>statistics book, this method provides excellent estimates if the sample 
>size is large, but in the cases I hope to be dealing with I will only 
>have a few samples and want to get as much information from them as I can.

>There has also been some discussion here about whether 
>there exist some values for the probabilities of the classes and the 
>probabilities of the various attributes given the class, which tells 
>you as much as possible from the given samples.  The methods I have 
>seen require a prior distribution and show you how to determine the 
>posterior distribution after seeing each example.  One then chooses a value 
>from this distribution using their favorite function, such as mean, median, 
>or mode, or equivalently by using some loss function.  It seems that their 
>is no value for the probabilities which will give you as much
>information as possible about the samples without chosing some
>type of loss function.  Is this correct and is there some way to 
>prove if it is or is not correct?

To do Bayesian statistics "correctly" requires that one sets up a prior
measure on the collection of states of nature and a loss function, and
then uses that procedure which minimizes the expected loss.  Now it is
a physical impossibility to do this accurately.  Fortunately, there are
robustness results which point out that certain approximations may do a
good job in certain situations.  Using maximum likelihood estimators to
approximate parameters may or may not be robust.

With a sufficiently large sample size, one can always do a better job.
But the largest sample size is not any better than knowing the distribution.

The prior measure and the loss function come from the user, and there is
no dictum which can be given as to how to set these up.  Now there are 
packages on the market which claim to do this for the user with little
input; they should be used only with the greatest of suspicion.  
-- 
Herman Rubin, Dept. of Statistics, Purdue Univ., West Lafayette IN47907-1399
Phone: (317)494-6054
hrubin@snap.stat.purdue.edu (Internet, bitnet)  
{purdue,pur-ee}!snap.stat!hrubin(UUCP)
Newsgroups: comp.ai,comp.ai.genetic,rec.games.programmer
Newsgroups: comp.ai
Subject: Re: Fuzzy vs. PID papers
From: erik@maui.til.com (Erik Horstkotte)
Date: Thu, 19 Nov 1992 17:24:42 GMT
Organization: Togai InfraLogic, Inc.
Keywords: Fuzzy

In article <olina.1.0@%canc_hs@sasb.byu.edu>, olina@%canc_hs@sasb.byu.edu (Olin Atkinson - Lab TA) writes:
|> 
|> 	I need to find some papers on Fuzzy logic vs. PID for a research 
|> paper.  I know there are some out there but I can't find any that I can 
|> access over the net.  I don't have modem access.  The official topic of the 
|> paper is Fuzzy vs. PID for control involving simulated human response.
|> 
|> Thanks.

The Fall 1991 issue of our company newsletter contained an article
that described some research we did into fuzzy motor control vs. PID
motor control.  You can either grab the entire PostScript(tm) file
for the entire newsletter (v1i2.ps.Z) or just the ASCII text file for
the article (v1i2motr.txt).  There is also a fairly complete list of
magazine articles dating between 6/91 and 10/92 that mention fuzzy
logic or fuzzy expert systems (art6.91.txt).  This might of use in
your research.

I know of at least three ways that you can pick up any of these
files:

1. You can get them from our fuzzy logic mail server.  Send a message
   to fuzzy-server@til.com, with just the word help in either the
   Subject: line or the message body (not both, or you'll get the
   help twice!).  The server will send back a short set of
   instructions on how to use it.

   To save you a couple of iterations, you could send the following
   message:

       help
       list
       compress
       send v1i2.ps.Z
       send art6.91.txt

2. You can get them from Tim Butler's new fuzzy logic repository,
   which is an anonymous ftp site ntia.its.bldrdoc.gov.  If you have
   trouble using this site, send email to tim@its.bldrdoc.gov.

3. You can get them via Tim Butler's email server.  Send a message to
   rnalib@its.bldrdoc.gov with "@@ help" as the subject or message
   body.  Again, send email to tim@its.bldrdoc.gov if you have
   problems.

4. You can just send me a message explicitly requesting them, and
   I'll email it to you directly.

Good luck with the research.
-- 
Erik Horstkotte, Togai InfraLogic, Inc.
The World's Source for Fuzzy Logic Solutions (The company, not me!)
erik@til.com, gordius!til!erik - (714) 975-8522
info@til.com for info, fuzzy-server@til.com for fuzzy mail-server
Newsgroups: comp.ai
From: John_Somerville@mindlink.bc.ca (John Somerville)
Subject: Re: Prolog compiler for PC
Organization: MIND LINK! - British Columbia, Canada
Date: Sat, 21 Nov 1992 00:35:54 GMT

On my BBS usenet.comp.lang.prolog is not available. This is probably true for
others also.
regards john
--
john somerville B.C. Hydro
affiliations FIG Forth Interest Group
From: corleyj@helium.gas.uug.arizona.edu (Jason D Corley )
Newsgroups: comp.ai
Subject: Re: Chess and AI
Date: 19 Nov 92 18:43:03 GMT
Organization: University of Arizona, Tucson, AZ

In article <92323.152822JJH113@psuvm.psu.edu> JJH113@psuvm.psu.edu (Your Puerto Rican neighbor!) writes:
>I need algorithms on how to implement a Chess game using LISP or any
>other AI computer language.  Please let me know if have information
>or a reference where I can look for.
>Thanks.
>Jose

I think this raises an interesting point-- if, someday, we do
truly achieve artificial intelligence, does it necessarily follow
that it will be able to play chess at grandmaster level?  I
know plenty of intelligent people who can't play chess worth a
lick.  I think it was Hofstadter who once mentioned that a true
AI program might say "I'm sick of chess, I like Monopoly better."

We could give the AI a chess-playing subprogram inside it,
but then it would be no better than a human with a chess
computer helping it!

A lot of people hold the misconception that Artificial Intelligence
means automatically that we will have Artificial Genius and the
computers will all "be smarter than us", when in reality, I
envision some AIs making mistakes and doing some really stupid
things...simply because they ARE intelligent and not automatons.

	Just a thought,
	Jason