From: neuron-request@CATTELL.PSYCH.UPENN.EDU ("Neuron-Digest Moderator")
Newsgroups: comp.ai.neural-nets
Subject: Neuron Digest V10 #19 (discussion + jobs)
Date: 19 Nov 92 16:18:06 GMT
Reply-To: "Neuron-Request" <neuron-request@cattell.psych.upenn.edu>
Distribution: world
Organization: University of Pennsylvania

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
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----------------------------------------------------------------------

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]
*****************************************