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AIList Digest Volume 8 Issue 071
AIList Digest Tuesday, 30 Aug 1988 Volume 8 : Issue 71
Query:
Modelling of spatial knowledge, Dr. Benjamin Kuipers
Responses:
Category Theory in AI
How do I learn about AI, Prolog, and/or Lisp?
Speech recognition with neural nets
Expert Systems for Statistical Analysis
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Date: Sun, 28 Aug 88 12:56 EDT
From: WHANG@HULAW1.HARVARD.EDU
Subject: Request on the modelling of spatial knowledge!
Hi, there!
Does anybody know the computer mail address of
Dr. Benjamin Kuipers? He was a profesor in
the Department of Mathematics at Tufts University
But I am not sure he is still there. I'd like to get
some information about his research on the "modelling of
spatial knowledge". Does anybody know about the "TOUR
model" of the cognitive spatial description? Of if you have
some information in this line of research;
the "reapresentation and modelling of spatial knowledge",
please, let me know!
whang at husc3 ( whang@husc3 ) BITNET
whang@husc3.harvard.edu (ARPANET)
Sang-Min Whang
Department of Psychology
33 Kirkland St,
Harvard University
Cambridge, MA 02138
Thank you for your attention!
Sang-Min.
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Date: 22 Aug 88 15:35:13 GMT
From: linus!philabs!hen3ry!dpb@husc6.harvard.edu (Paul Benjamin)
Subject: Re: Category Theory in AI
In a previous article, Jack Campin writes:
>I can't imagine what category theory has to contribute to knowledge
>representation (though I can just about imagine it helping to describe
>neural nets in a more abstract way). Can the philabs people say more
>about what they're up to?
Well, not really, in a public forum. But Mike Lowry of the Kestrel
Institute has pointed out that a representation can be viewed as
a category, and a shift of representation as a morphism. The
question of whether this insight is very productive is open, but at
least it gives us a formal notion of representation, and we've
built on this some formal notions of abstraction and learning.
We'll let you know if this turns out to be fruitful.
Paul Benjamin
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Date: 22 Aug 88 21:03:24 GMT
From: sco!johnwe@uunet.uu.net (John Weber, Celtic sysmom)
Subject: Re: How do I learn about AI, Prolog, and/or Lisp
In article <398@mfgfoc.UUCP> mike@mfgfoc.UUCP (Mike Thompson) writes:
<...>
>I have three question which I hope one of you can answer:
>
>1. I have an IBM/XT at home with the newest version of TURBO PROLOG.
>Can I use this system to gain an understanding of AI applications
>such as expert systems? If so, what books can help me? I have not
>seen Turbo Prolog mentioned in this newsgroup and I fear that
>it is considered by experts to be a toy Prolog or an implementation
>so neutered as to be worthless.
(Creak... Damn, this asbestos suit is getting stiff...
ZIP! Humm... Enough nitrogen. Hisssss... POP! Foosh...)
My exerence with Turbo "Prolog" was extermely negative. It
may be a useful language, but I kinda doubt it. It doesn't
support such things as asserting predicates into the data
base, the syntax isn't C&M, and it is strongly typed. It
is also extremely slow.
(Click.)
If you can get a hold of C-Prolog or SB-prolog, they are
quite acceptable and useful implementations. These are
for UN*X. Arity Prolog is a good commercial prolog for
the IBM PCish boxes.
>2. Does anyone know of classes offered in my area (I live in Los Altos,
>California) at local colleges which would teach me Prolog? I have already
>checked local community colleges, but their classes are only on
>languages such as Fortran, Cobal, Pascal or 'C'. Would I be better taking
>a more general class on AI instead of a specific language? Should I
>consider Lisp over Prolog? (It came with GNU Emacs and is available on
>my Unix system at work.)
Lisp and Prolog address different language issues, and are
both good and useful languages. Prolog is quite different
from most "normal" languages, and may pose certain learning
difficulties. My personal favorite Lisps are Kyoto Common
Lisp and MIT C-Scheme. They are for UN*X, again. There
is a Scheme dialect for Macs, but I've never played with it.
Microsoft has a Lisp for MS-DOS (supposedly it is Common
Lisp, but again, I haven't played with it). Emacs Lisp
is useful in the context of Emacs, but I don't think it
would make a good way to learn lisp.
I personally like Lisp more than I like Prolog, but that
is a taste thing. Lisp can also be much faster.
Oh, are you on a 4.* BSD box? If so, there may be Franz Lisp
floating around your bin directories. Sun also has a really
good Lisp package (or so I'm told).
I thought De Anza Jr. College offered an AI class which
taught Lisp, but it's been a while since I took a class
there.
>3. What is the best way to get introduced to the AI field? I'm I
>taking the right approach? Any comments would be appreciated.
>
>Thanks in advance.
>
No sweat.
>Mike Thompson
>
>---------------------------------------------------------------------------
>Michael P. Thompson FOCUS Semiconductor Systems, Inc.
>net: (sun!daver!mfgfoc!engfoc!mike) 570 Maude Court
>att: (408) 738-0600 Sunnyvale, CA 94086 USA
Please note: these are my own opinions, and in no way reflect
the opinions of my employers.
--
#############################################################################
# # #
# "In the fields of Hell, # John Weber, ...!uunet!sco!johnwe #
# where the grass grows high, # @ucscc.ucsc.EDU:johnwe@sco.COM #
# are the graves of dreams, # #
# allowed to die." -- Author unknown # Celtic sysmom with an ATTITUDE! #
# # Any opinions expressed are my own #
#############################################################################
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Date: Tue, 23 Aug 88 16:32:36 -0200
From: Antti Ylikoski <ayl%hutds.hut.fi%FINGATE.BITNET@MITVMA.MIT.EDU>
Subject: Speech recognition with neural nets
In AIList Digest V8 #63,
att!chinet!mcdchg!clyde!watmath!watvlsi!watale!dixit@bloom-beacon.mit.edu
(Nibha Dixit) writes:
>Subject: Speech rec. using neural nets
>Is anyody out there looking at speech recognition using neural
>networks? There has been some amount of work done in pattern
>recognition for images, but is there anything specific being done
>about speech?
In the Helsinki University of Technology, in the Department of Technical
Physics, the group of Professor Teuvo Kohonen has been studying the
usage of neural nets for speech recognition for several years.
Professor Kohonen gave a talk on their results in the Finnish AI
symposium in this year. They have an experimental system which uses a
neural net board in a PC. I cannot remember whether the paper is
written in English or in Finnish, but should you wish to get the
symposium proceedings, contact
Finnish Artificial Intelligence Society (FAIS)
c/o Dr Antti Hautamaeki
HM & V Research
Helsinki, Finland
I understand Kohonen's results are comparable to other approaches to speech
recognition.
--- Andy
------------------------------
Date: Sun, 28 Aug 1988 21:05-EDT
From: Kai-Fu.Lee@SPEECH2.CS.CMU.EDU
Subject: Speech rec. using neural nets
In response to Nibha Dixit's question about speech recognition using
neural networks, I would recommend the following two articles by
Richard Lippmann:
An Introduction to Computing with Neural Nets, IEEE ASSP Magazine,
Vol. 4, No. 2, April 1987.
Neural Nets for Computing, IEEE International Conference on Acoustics,
Speech, and Signal Processing (ICASSP), April, 1988.
The ICASSP conference proceedings contain quite a few interesting
papers on speech recognition with neural networks.
Kai-Fu Lee
Computer Science Department
Carnegie Mellon University
Pittsburgh, PA 15213
------------------------------
Date: Mon, 29 Aug 88 11:19:19 EST
From: cik@l.cc.purdue.edu (Herman Rubin)
Subject: Re: Expert Systems for Statistical Analysis
In a previous article, KDM2520@TAMSIGMA.BITNET writes:
> If anyone on the list is aware of any commercial expert systems which do
> statistical analysis, I sure would appreciate the information. I am looking
> for expert statistical analysis packages which process data, analyze
> correlation etc., forecast trends, detect regeneration cycles, and so on.
> I have looked through AI Magazine, IEEE Expert and several Computer journals
> and I couldn't see any such product advertisements. Could someone who is
> aware of such expert statistical analysis packages send me the info please?
>
> Thank you. MURALI@TAMLSR (bitnet)
There are things that a computer is capable of doing, but this is not one of
them. Statistics is not a black box into which one can put data and come out
with the state of the universe.
To analyze a problem, it is necessary for the user to input a model, or better,
a collection of models. The user must realize that many assumptions must be
made. It is advisable to have a good mathematical statistician available to
point out the consequences of the model which the user does not realize have
been inserted. Analyze correlation indeed! It is extremely rare that
correlation has anything to do with the real problem.
In addition, the user must have an evaluation of the consequences of an
incorrect action. Massive statistical uncertainty may be irrelevant if the
resulting action is unaffected, and small uncertainty may be very important
if the effects of a wrong action are sufficiently great. I personally have
worked on this problem, and the difficulties are major.
Statistical packages of the type to use this input, when well formulated, are
still in the development stage.
--
Herman Rubin, Dept. of Statistics, Purdue Univ., West Lafayette IN47907
Phone: (317)494-6054
hrubin@l.cc.purdue.edu (Internet, bitnet, UUCP)
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End of AIList Digest
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