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Neuron Digest Volume 10 Number 19
Neuron Digest Thursday, 19 Nov 1992 Volume 10 : Issue 19
Today's Topics:
Re: Help on hybrid systems
Stock Market
Faculty position at NYU
4 research posts
Research enquire
FYI: Results of Physics of Computation Workshop
Send submissions, questions, address maintenance, and requests for old
issues to "neuron-request@cattell.psych.upenn.edu". The ftp archives are
available from cattell.psych.upenn.edu (130.91.68.31). Back issues
requested by mail will eventually be sent, but may take a while.
----------------------------------------------------------------------
Subject: Re: Help on hybrid systems
From: Dave Cornforth <djc@Cs.Nott.AC.UK>
Date: Fri, 13 Nov 92 10:55:40 +0000
Don't know much about your field, but here's my two cents worth...
If you already have some firm rules which are sound, then why not use them
directly in your system?
If you have some decisions which are a bit more "wooley", then you could
look at a neural network to cope with those. However, I would suggest you
do some kind of statistical analysis on your data first. If you find that
you have data which is roughly normally distributed and unimodal for each
class, which you want to assign to different classes (or decisions), then
you can't beat a Gaussian model Bayesian classifier.
If the data is not normally distributed, or multi-modal, then you could look
at "real" neural networks, but there are also some jolly good memory
table-based classifiers which tend to be a lot quicker to train.
Dave
------------------------------
Subject: Stock Market
From: P.Refenes@cs.ucl.ac.uk
Date: Fri, 13 Nov 92 10:04:10 +0000
I am afraid I have not followed this topic very closely, but here are
some references of our own work in teh field:
[1] Refenes A. N., Zapranis A., and Azema-Barac M., "Stock
Ranking: Neural networks Versus Multiple linear
Regression", Proc ICNN'93 San Francisco (submitted
1992).
[2] Refenes A. N., et al "Currency Exchange rate prediction
and Neural Network Design Strategies", Neural computing
& Applications Journal, Vol 1, no. 1., (1993).
[3] Refenes A. N., & Zaidi A., "Managing Exchange Rate
Prediction Strategies with Neural Networks", Proc.
Workshop on Neural Networks: techniques & Applications,
Liverpool (Sept. 1992), also in Lisboa P. G., and
Taylor M, "Neural Networks: techniques & Applications",
Ellis Horwood (1992).
[4] Refenes A. N., & Azema-Barac M., "Neural Networks for
Tactical Asset Allocation in the Global Bonds Markets",
Proc. IEE Third International Conference on ANNS,
Brighton 1993 (submitted 1992).
[5] Refenes A. N. et al "Financial Modelling using Neural
Networks", in Liddell H. (ed) "Commercial Parallel
Processing", Unicom, (to appear).
------------------------------
Subject: Faculty position at NYU
From: ltm@cns.nyu.edu (Laurence T. Maloney)
Date: Sun, 15 Nov 92 20:02:07 -0500
N N Y Y U U
* NN N Y Y U U *
* * N N N Y U U * *
* N NN Y U U *
N N Y U U U
JOB OPPORTUNITY
TENURED OR TENURE-TRACK
COGNITIVE SCIENCE/COGNITIVE PSYCHOLOGY/COGNITIVE NEUROSCIENCE -- NEW YORK
UNIVERSITY: The Department of Psychology, Faculty of Arts and Science,
New York University anticipates making faculty appointments beginning
September 1993, in one or more of the above areas. These are tenured or
tenure-track position and the rank is open. Candidates must be engaged in
an active research program at the forefront of modern cognitive
psychology, cognitive science, or cognitive neuroscience. Senior
applicants should submit a vita. Others should also include reprints of
recent publications and three letters of reference. Applications should
be sent to Professor Murray Glanzer, Department of Psychology, 6
Washington Place, Room 965. TO ENSURE CONSIDERATION, APPLICATIONS SHOULD
BE RECEIVED BY JANUARY 15, 1993. New York University is an Equal
Opportunity/Affirmative Action Employer.
Brief questions? E-mail to Larry Maloney, ltm@cns.nyu.edu.
------------------------------
Subject: 4 research posts
From: Noel Sharkey <N.E.Sharkey@dcs.ex.ac.uk>
Date: Mon, 16 Nov 92 11:36:21 +0000
Research Posts
at
Centre for Connection Science
Department of Computer Science
University of Exeter
UK
Four new research posts will be available (expected start January 1st,
1993) at the Centre for Connection Science, Department of Computer
Science, as part of a 3-year research project funded by the SERC/DTI and
led by Noel Sharkey and Derek Partridge. The project will investigate
the reliability of software systems implemented as neural nets using the
multiversion programming strategy.
Two of the posts will at the post-doctoral level (grade 1A). The ideal
applicant will be proficient in both neural computing and software
engineering (although training in one or the other may be given). In
addition, there is a requirement for at least one of the successful
applicants to work on the formal analysis of network implementation as a
paradigm for reliable software.
The other two posts will be for Research Assistants/Experimental Officers
at grade 1b. One of these will be required to have a high level of
proficiency in C programming and general computing skills. The other
will be part-time, and preference will be given to an applicant with good
mathematical and engineering skills (particulary control systems).
For more information please contact Lyn Shackelton
by email (lyn@dcs.ex.ac.uk or by telephone
(0392-264066 mornings 10.00-2.00).
------------------------------
Subject: Research enquire
From: LHOTAK@whmain.east-london.ac.uk
Date: 18 Nov 92 18:29:57 +0000
Dear reader,
My name is Martin Lhotak and I currenly became a PhD. student at the
University of East London. The topic of my PhD concerns with a model of
an artificial intellect based upon classification paradigm and self-
organizing hierarchy establishment and a short proposal summary of my
PhD. topic follows:
=< Start of my PhD. proposal>===================================
Title: A model of an artificial intellect based upon
classification paradigm and self-organizing hierarchy
establishment
The PhD. research would investigate the principles of human intellect and
the generic intellectual processes in systems leading to qualified
understanding of the world the system is based in.
Current achievements in this area have recorded just a partial success
due to the approach to modell the intellectual process by large amount of
rules, data, formulas,etc., which tends to be valid only under specific
conditions.
In my understanding those attributes (facts, data, formulas) do not
represent intelligence, but only support and monitor the development
process of a given intellect. In my PhD research I would like to look at
the aforementioned process from the point of view of how the organization
of a system changes during the information gathering process and how
significant it is to gather information from various independent (often
contradictory) sources.
Especially, I would like to focus on the essential principles, e.g.
classification and hierarchization, which, I believe, helps human
intellect to cope with complex tasks. Based upon the theory of object
classification and the results observed from the general information
gathering process I would like to compose a prototype of an adaptive
intelligent system capable of autonomous classification and autonomous
establishment of hierarchies in order to "understand" the meanings of
given "model world" objects.
The theoretical model would require continuous testing on a given set of
subject domains, e.g. Plant Fossil Record - a large heterogeneous data
set, etc.
==< End of my proposal >========================================
As you have quite likely observed my PhD. topic is rather generous (and
perhaps too ambitious) and it is highly probable that I would be more
specific on the PhD. registration form after I would do some preliminary
research.
I realize that the aforementioned proposal is fairly vague and
"nothing-specific-saying", however, some essential ideas should be
visible and I would be very grateful for any (especially critical)
comments on my approach or proposal for my PhD. studies and any
information whether anyone has tried (or rejected) similar approach or
whether anyone is already doing similar research in this area.
I would be also very thankful for any possibility of consulting and
discussing my ideas directly, via e-mail, or in a sort of a larger
scientific arena (listservers?, meetings?).
The best way how to contact me is via e-mail:
lhotak@whmain.uel.ac.uk
Best Regards,
o
#/-
Martin Lhotak # \-/|
#/-\ |
==============================================================# \-/
Martin Lhotak # eMail: lhotak@whmain.uel.ac.uk #
Systems & Computing # sMail: 39, Lodge Avenue #
University of East London # Dagenham, RM8 2JD #
United Kingdom # telNo: 081-590-7722 ext. 4101 #
===============================================================
------------------------------
Subject: FYI: Results of Physics of Computation Workshop
From: Doug Matzke <matzke@hc.ti.com>
Date: Thu, 12 Nov 92 19:12:54 -0600
Hello
The Physics of Computation Workshop was held on October 2-4, 1992 in
Dallas Texas, and was attended by almost 100 people from industry,
press, university, and government agencies. The attendees decided to:
1) Publish a post-proceedings of the papers with IEEE Press
(see order form below to reserve you own copy - about 500 pages)
2) Start an electronic mailing list on the physics of computation.
(Please send requests to physics.computation-request@hc.ti.com)
3) Have the next conference in two years.
4) Start publishing general articles to establish the field.
One of the attendees is a science writer for the Dallas Morning News,
and the text of his article is included to give you some sense of what
happened at the workshop.
So get involved with this emerging field by signing up with the mailing
list, ordering your own copy of the post-proceedings, and making plans
to attend the next conference.
Doug Matzke
Workshop Chairman
EMAIL: matzke@hc.ti.com
PHONE: (214) 995-0787
*********************************************************************
Order information for Post-Proceedings for
Physics of Computation Workshop
(Held on October 2-4, 1992 Dallas Texas)
These post-proceedings are available at the prepublication rate of $35
(US Dollars), if your order is received by December 14, 1992, along
with this form. If you order at the the conference rate, the book will
be mailed to you directly from the printer.
The Post-Proceedings will be available for purchase after publication,
from the IEEE Computer Society Press, probably at a higher cost.
NAME: ________________________________________________________________
ADDRESS:______________________________________________________________
CITY:___________________________________________ STATE:_______________
COUNTRY: _____________________________________ ZIPCODE:_______________
COPIES: ______________ X $35.00 = TOTAL AMOUNT: ______________________
Include check or money order for the full amount, made out to:
Dallas IEEE Computer Society
(No credit cards or COD, please.)
Send this Completed form with check or money order to:
Douglas Matzke
Post-Proceedings Order for PCW
Texas Instruments
P.O. BOX 655474, MS 446
Dallas, Tx 75265
Questions may be directed to Doug at (214)995-0787 or matzke@hc.ti.com
*********************************************************************
As appeared in Dallas Morning News
Monday October 26, 1992
OPENING THE DOOR TO COMPUTER PHYSICS
New field may solve mysteries about universe, time, genes
By Tom Siegfried
Some physicists can't get their minds off computers.
Perhaps that's because minds seem to work a lot like like computers.
Understanding the physics of how computers compute, some scientists
reason, might provide clues to how brains do it, too.
And even if it can't explain the the brain, the physics of computing
may solve mysteries about the universe, the genetic code and why time
always flows in one direction.
At least those were among the topics discussed this month when
researchers from around the world met in Addison to explore links
between basic physical laws and the process of computation.
Nearly 100 researchers from physics, computer science, mathematics and
related fields shared insights on computers, quantum physics, black
holes and the brain. Some speakers discussed using information theory
to study problems in molecular biology or the working of human memory.
Others showed how quantum theory can be used to devise better secret
codes. Some speakers even described real physics in real computers.
After all, Texas Instruments Inc. of Dallas sponsored the conference.
At one level, studying the physics of computing does have a practical
aspect. Knowing basic physics is critical in designing smaller, faster
computer chips that won't melt down by producing too much heat. But
speakers at the Addison meeting often focused on more theoretical
questions, ranging from how to design a foolproof code for automates
teller bank cards to whether the universe is a gigantic computer
simulation.
The diversity of the discussions suggested that while a new
scientific discipline has been born, it's too soon for a christening.
The new field is related to information theory, computer science,
artificial intelligence, chaos and fractals, but it doesn't really have
a name of its own.
"It's clear that this field is not well defined," said Tommaso
Toffoli of the computer science labaratory at the Massachusetts
Institute of Technology.
Researchers addressing this identity crisis could only conclude that
the new field concerns itself with "fundamental connections between
physics and computation."
At the heart of this connection is an obscure but important rule
called the Landauer principle. It involves how much energy a
computation requires.
More than three decades ago, IBM computer physicist Rolf Landauer
calculated the least amount of energy needed to perform a single
computational step. The answer, he showed, is essentially zero. If a
computation is performed slowly eneough, the amount of energy used up
can be as small as desired.
That was a surprising result. Transferring information in a computer
is like sending a message from one memory location to another, and
physicists used to think that sending messages required energy. But the
early studies took too limited a view of information transfer, usually
considering signals sent by waves.
"We don't have to send information by waves," said Dr. Landauer. "I
can send you a floppy disk. If I'm desperate I can use the U.S. Postal
Service."
But even in computers, there's no free lunch. The catch is that
computers have limited memories, so information has to be erased from
time to time. And the Landauer principle, published in 1961, states
that erasing information must use some minimum amount of energy.
"Discarding information involves an unavoidable energy penality," Dr
Landauer said at the Addison meeting.
Landauer's principle places a theoretical limit on how
energy-efficient a computer can possibly be. The principle doesn't
matter much for today's real-life computers, which use much more energy
than the theoretical minimum.
But the principle came into play in numerous presentations at the
Addison meeting, on topics ranging from black holes to the brain.
For example, Christopher Fuchs of the University of North Carolina at
Chapel Hill analyzed a peculiar method of erasing information with a
black hole, a region of space around the remains of a collapsed star.
Since the gravity of a black hole is too strong to permit anything
within it to escape, a bit of information dropped into a black hole is
lost forever.
Does Landauer's principle apply when the information eraser is a black
hole? Dr. Fuchs thinks so. A black hole swallowing a bit of
information should grow in surface area, and Dr. Fuchs calculated that
the amount of growth is roughly what would be expected if Landauer's
principle is obeyed.
David Wolpert, of the Santa Fe Institute in New Mexico, invoked
Landauer's principle in explaining why the brain can only remember the
past - unlike King Arthur's pal Merlin the Magician, who remembered the
future.
Dr. Wolpert tried to show how the psychological sense of time's
one-way flow is related to the direction of time that arises from the
second law of thermodynamics.
Several speakers at the meeting discussed that law, which says, in
essence, that disorder wins out over order. In other words, an
organized system left to itself, will become disorganized. As time goes
forward, eggs break but don't reassemble, building decay and machines
wear out.
The second law is widely regarded as among the most significant laws
of physics. But it turns out that Landauer's principle is needed to
save the second law from a demonic paradox.
The Scottish physicist James Clerk Maxwell proposed the paradox in
1871. More than a century passed before work by Dr. Landauer and IBM
colleague Charles Bennet explained it.
Maxwell considered the effects of the second law in systems where
something hot is separated from something cold. Open a door between a
warm room and a cold room, and soon the air molecules will mix and both
rooms will be the same temperature. The second law requires the mixing
to create maximum disorder, or entropy.
But Maxwell imagined a demon guarding the door between the rooms,
opening it to allow the fast, hotter molecules into one room and closing
it to keep the cold, slow molecules in the other. The demon could thus
keep the rooms at different temperatures, an apparent violation of the
second law.
Physicists long supposed that the demon needed energy to observe the
molecules and record information about their speed. The demon's energy
use would create more disorder than the order he created, saving the
second law.
But, as Drs. Bennet and Landauer showed, computing the speeds of the
molecules can be accomplished without using energy. Only when the demon
resets his computer to calculate the speed of the next molecule is
energy consumed, producing entropy to enforce the second law.
Still, some physicists continue to wonder whether a sufficiently smart
demon can outwit Dr. Landauer. Computer simulations to test new demon
strategies were reported at the meeting by Andrew Rex and Ross Larsen of
the University of Puget Sound in Tacoma, Wash.
While the second law is still presumed to be safe, there is a way
around Dr. Landauer's limit in computing - if a computer saves every
intermediate result of every computation. Such a computer could then
reverse every step, return to its starting place after carrying out a
computation with no net use of energy, as Dr. Bennet demonstrated in
1973.
But any computer keeping track of everything would need a huge memory.
Ultimately, the size of such a computer would be limited by the size of
the universe , Dr. Landauer pointed out.
"The size of the memory is probably limited in principle, and not just
by the size of your NSF (National Science Foundation) budget," he said.
Of course, nobody would really try to build a computer the size of the
universe.
On the other hand, maybe somebody has. said Edward Fredkin of Boston
University. He contends that the entire universe is just one big computer
simulation.
Physics, Dr. Fredkin asserts, is the constant processing of
information to convert a representation of the present into a
representation of the future.
"Life works like a computer, thinking works like a computer and maybe
physics works like a computer," he said.
Whoever built this computer is not of our universe, of course. We're
in the position of a pilot trainee flying from New York to Houston on a
computerized 747 simulator. The computer is not in New York or Houston,
but somewhere else.
In the same way, says Dr. Fredkin, we live in a simulated universe
running on a computer that is somewhere else.
Dr. Fredkin's view isn't widely accepted.
"I don't buy it," said physicist William Frensley of the University of
Texas at Dallas.
"I don't know if it's true or not," said physicist Seth Lloyd of Los
Alamos National Laboratory in New Mexico. "I certainly doubt it's true
in the sense that he (Dr. Fredkin) seems to think about it."
Other speakers at the conference applied lessons from physics and
computation to the mysteries of biology. Some presentations dealt with
the best-known information storage system in biology - DNA, the molecule
that makes up genes.
DNA's genetic information is copied by RNA molecules in a cell's
nucelus. The genetic information encoded in RNA molecules must then be
cut up and spiced together before cells can use that information to make
proteins. Thomas Schneider of the National Cancer Institute's
mathenatical biology laboratory in Fredrick, Md., reported studies using
information theory to understand how cells know when and where to
splice.
Several researchers tried to relate computational insights to the
working of the human brain. Some discussed how brains represent
information as patterns, others suggested ways that quantum physics
could be involved in consciousness.
Ordinarily, quantum physics describes the subatomic world where waves
can be particles and particles can be waves, depending on how an
experiment is set up. But whether quantum physics really has anything
to do with consciousness is still speculation. And schemes for using
curious effects of quantum physics in computing won't be showing up for
sale at the Incredible Universe anytime soon.
Dr. Lloyd pointed out thar quantum systems could in principle perform
computations, but doing so in practice would be difficult or impossible.
One quantum computing scheme, discussed by Richard Jozsa of the
University of Montreal, could in theory compute complicated problems
twice as fast as a standard computer. But you would only have a 50-50
chance of getting the answer to the question you asked.
"You can get Two computations for the price of one, but only half of
the time"," Dr. Jozsa said.
Several speakers described one potential practical use for quantum
physics - sending secret codes. Because quantum waves are disturbed by
observation, efforts by an eavesdropper to detect a secret message can
easily be detected. And an elaborate setup for sending and recieving
quantum information can guarantee the ability to transmit a code no
eavesdropper could possibly intercept.
Claude Crepeau of the Ecole Normale Superieure in Paris suggested that
the quantum coding scheme could be put to use in a bank card for use by
automated teller machines. The system could be set up so that the
password needed to use the card would be a perfect secret - nobody at
the bank would even need to know the password.
************************************************************************
Extra box with caption
Landauer's Principle vs. Maxwell's Demon
Scientists have gained insights into the basic physics involved in
computing -- or processing information -- by studying the connections
betweeen computing and the second law of thermodynamics.
That law syas that a natural system always tends to become more
disordered as time passes, unless energy is imported from the system.
No one has ever discovered a violation of this law.
But in 1871, the scottish physicist James Clerk Maxwell proposed a
paradox suggesting that a clever being, or "demon", might overcome the
second law's requirements.
Maxwell envisioned two chambers, one with hot air and one with cold
air. According to the second law, opening the door between the chambers
should cause the air molecules to mix, and bring both compartments to
the same temperature. But Maxwell suggested that a demon guarding the
door could open and close it selectively allowing the fast, hotter
molecules to collect on one side and keeping the slow, colder molecules
on the other side -- an apparent violation of the second law.
Physicists long supposed that the demon needed to import energy to
observe the molecules and calculate the necessary information about
their speed. The use of imported energy would generate diorder outside
the system to compensate for the order created inside, maintaining the
requirements of the second law.
But in recent years, studies by Rolf Landauer and Charles Bennet of
IBM have shown that copmuting the speeds fo the molecules can be
accomplished without using energy. But when the demon resets his
computer to calculate the speed of the next molecule, energy is
consumed, saving the second law.
The notion that discarding information requires the use of energy,
known as Landauer's principle, is a central consideration in a wide
range of current investigations about the physics of computing.
------------------------------
End of Neuron Digest [Volume 10 Issue 19]
*****************************************
