Subject: AIList Digest V5 #139

From: [email-masked]@vtcs1
Date: Thu, 11 Jun 87 15:49:06 edt

Date: Wed 10 Jun 1987 00:13-PDT
From: AIList Moderator Kenneth Laws <[email-masked]>
Subject: AIList Digest   V5 #139
To: [email-masked]
Reply-to: [email-masked]
US-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA  94025
Phone: (415) 859-6467

AIList Digest           Wednesday, 10 Jun 1987    Volume 5 : Issue 139

Today's Topics:
  Conference - AAAI's Preregistration Deadline,
  Binding - Number Theory Net,
  Queries - Small Expert Systems & Speech Data Compression &
    Dominoes & Hofstadter's Waking Up From the Boolean Dream,
  Theory - Applying AI Models to Biology

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Date: Thu, 4 Jun 87 10:23:18 PDT
From: AAAI <[email-masked]>
Subject: AAAI's Preregistration Deadline

The AAAI would like to remind those individuals interested in attending
AAAI-87 in Seattle, July 13-17, that the preregistration deadline of Friday,
June 12, draws very near. If you would like registration materials, please
call or send us a msg with your name and mailing address.  Thanks!

AAAI
445 Burgess Drive
Menlo Park, CA 94025
(415) 328-3123
[email-masked]

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Date: 5 Jun 1987 16:45:12-EDT (Friday)
From: "Victor S. Miller" <[email-masked]>
Reply-to: [email-masked]
Subject: Number Theory Net

                [Forwarded from the Stanford bboard.]

          Announcing Number Theory Net
   I would like to start a separate network for Number Theorists
around the world.  This would be similar in principle to Theory Net (and
probably have some overlap).  The purpose of NumberTheory Net would be
to help communication among those who work in number theory.  Appropriate
submissions would be: problems, solutions, queries, notification of
address changes, announcement of results, etc.  For now, all submissions
will be handled by the same userids as for TheoryNet: [email-masked]
or [email-masked] for submissions, and [email-masked]
or [email-masked] for administrative matters (e.g. additions or
deletions to the subscriber list, requests for back submissions, etc.).
All contributions should be clearly labeled as being for NumberTheoryNet.
I think that it should be useful and enlightening.
                    Victor S. Miller -- moderator

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Date: 5 Jun 87 13:52:47 GMT
From: [email-masked]  (Sharon Salveter)
Subject: Need small expert system for research

I am directing a research project on knowledge transfer for expert
systems.  Essentially, we are trying to automate the function of
the knowledge engineer in classification-type expert systems. We
are looking for small (fewer than 1000 rules) existing expert systems
to use as our domains and testbeds/benchmarks.  If you have such a system
that you would like to donate to research, please contact me.

Sharon Salveter  Computer Science  Boston University

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Date: 2 Jun 87 22:10:53 GMT
From: [email-masked]  (Rob Peck)
Subject: Speech Data Compression

I am interested in finding some kind of data compression algorithm
that is suitable for compressing speech data.  As I understand it,
human speech has a great deal of redundancy to it, i.e. repetitions
of virtually the same waveforms over a period of time, as well
as slow changes in many cases from one waveform to the next.

However, if one takes a set of audio samples of a spoken word,
the samples will not fall in the right spots to show up any such
redundancy.  Thus, for a simplistic compression algorithm that
looks for repeated sequences, no opportunity to compress would
be noticed.

Could someone point me to the appropriate literature?   Or is there
some public domain source code that is already available for this?

The code needn't be fast on the analysis and compression.  On
playback, it should be pretty easy to expand, though.  That is,
play so many repetitions of this waveform at this sampling rate,
then do this next one (or better still, adjust the current waveform
until it looks like this new one, as a slewing to the new output...
that'd be neat).

I've read a little about FFT's, but once calculated, I have no
idea how to use it or if it gives me remotely what I am looking
for here.

Please EMAIL directly to me.  I will summarize any interesting
responses to the Net.   Thanks very much.

Rob Peck        ...ihnp4!hplabs!dana!rap

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

Date: 8 Jun 87 19:46:16 GMT
From: [email-masked]  (Jorge Gautier)
Subject: WANTED: references on the game of dominoes

I am looking for references on computer implementations of the game of
dominoes.  I suspect there are many variations on the rules for this game,
but any pointers to papers, commercial products, Ph.D. theses :-), etc.
would be much appreciated.  Please reply by mail.

Jorge Gautier
[email-masked]

"America is waiting for a message of some sort or another."

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

Date: Tue, 09 Jun 87 11:26:42 n
From: [email-masked]
Subject: digging up the garbage....

Ok, here's a quick query for old timers on the AIList (no prizes KIL for
being the first in line). Did the list ever show much of a response to
Doug Hofstadter's "Waking up From the Boolean Dream or, Subcognition as
Computation" ? Yes, yes - I know thats it a wet, cloudy, amorphous piece
of writing, utterly unpublishable in any journal beginning with the
name "Transactions of....", but nevertheless, Hoftstadter's criticism
of 'traditional' AI ("high church computationalism") still seems well in
place amidst the countless "has anyone seen expert system EXSYS yet ?"
and "any clues on dealing with uncertainty within the context of a
WHITEWASH based frame-solving fourth generation language ?" that
dominate the list......

I don't want to dig up the past, but if it hasn't happened before, are there
any defenders of the EXSYS/4GL/"fuzzy reasoning"/etc., etc., approach willing to
correct my impressions of the right direction for movement ?
Or even just give me a few recent, decent rebuffs to Hofstadter's viewpoint ?

yours in statistical emergence,

paul davis

"i wash my own clothes, i wash my own hair, i wash my own opinions"
nb: but my employers provide the washing machine, the shower & the computer.

[email-masked]

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Date: 6 Jun 87 01:38:26 GMT
From: [email-masked]  (Craig D. Hubley)
Subject: Taking AI models and applying them to biology...

Forgive the wide cross posting, net.gods, but I am interested in gathering
an opinion from biological and artifical intelligence people on a model
that arises from AI but has (possibly) biological implications:

Foreword or WHY I'M WRITING THIS.
--------------------------------
I was semi-surprised in recent months to discover that cognitive psychology,
far from developing a bold new metaphor for human thinking, has (to a degree)
copied at least one metaphor from third-generation computer science.

This description of the human memory system, though cloaked in vaguer terms,
corresponds more or less one-to-one with the traditional computer
architecture we all know and love.  To wit:

        - senses have "iconic" and "echo" memories analogous to buffers.
        - short term memory holds information that is organized for quick
        processing, much like main storage in a computing system.
        - long term memory holds information in a sort of semantic
        association network where large related pieces of information
        reside, similar to backing or "archived" computing storage.

At least this far, this theory appears to owe a lot to computer science.
Granted, there is lots of empirical evidence in favour, but we all know
how a little evidence can go far too far towards developing an analogy.

What I think we may need are good parallel connectionist computing models
for the social sciences to copy, rather than these old ones that we are
beginning to fuse and modify and discard.  After all, engineering can
construct and test artifacts much quicker than psychologists can.  And
investigate their insides and their performance as well...

The Point or WHAT I'M THINKING ABOUT
------------------------------------
        Single cells are constructed according to instructions resident
        in their own DNA.  When their reproductive process fails, they
        die, become cancerous, etc...

        In computing terms, a self-reproducing program messes up the code
        and therefore fails to function (it does not reproduce).  Or, it may
        continue to reproduce a flawed cell (cancer...).

        But a biological mechanism such as, say, a muscle or a brain is
        a massively parallel system consisting of many many redundant cells,
        each of which is capable of performing (at least almost) the same
        function.

        So many many parts would have to fail before the effect was enough
        to endanger the system as a whole.  That is, it degrades gracefully.
        This effect has been observed in parallel sensing systems, which
        use several low-resolution phased fields that redundantly cover
        the same area.  Removing one such field results in a loss of
        resolution, but not utter failure to detect a stimulus.  Details
        in Geoffrey Hinton and others... (Byte AI issue, 1985?)

        At some point of degradation, the whole parallel system will collapse.
        Or an aged human being will die of a cold.

The Question or WHAT DO YOU THINK?
----------------------------------
Apparently, all human organ weights begin to decline shortly after puberty.
The cumulative effect of this seeming reduction of resources isn't felt so
strongly until middle-age, when we become more susceptible to disease.

So far, this is just a statement of the nature of parallel systems.

But does it hold up as a theory of aging?

- Is mitosis sufficiently prone to failure to account for organ decline?
        - Statistically, one would expect exponential distribution for
        failure of single cells, the rate dependent on mitosis failure,
        and perhaps modified by other cell-killing factors
        - Does organ failure, medically, occur at the point where
        a parallel processing system, mathematically, would fail?

I've heard that mammal cells appear to suffer a "hard" reproductive limit
of 52 mitosis operations, and that meiosis "resets this counter" to 0.

- any comment on this, bio-med types?  Is it true?
- Would a theory assuming a simple variable or random "counter" in each cell
limiting its reproductive span better explain aging (programmed cells...)

It doesn't seem so... regardless of the origin of the failure, the observed
degradation of the system as a whole would still follow this pattern.

The upshot of this is that a potentially useful life science model may have
just materialized in artificial intelligence.

The main flaw that I can see in it is that a cell is complex mechanism in
and of itself, and so the success/failure of each might be subject to
many factors in parallel as well.  That is, it might not fail the way a
short subroutine would were it copied badly, which is the gist of this.
But then one might find a lower level where the parts were sufficiently
monolithic that the analogy held.

This seems to kick the butt of the good old 'Entropy' theory... cop-out.
Incompentent nineteenth century philosophers leaned heavily on entropy.

Comments?  Flames?  The name of a good shrink?

Musing,
Craig.

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

Date: 10 Jun 87 02:49:55 GMT
From: [email-masked]  (Anthony Pelletier)
Subject: Re: Taking AI models and applying them to biology...

(Craig D. Hubley) writes:
(cognative psycology)
>far from developing a bold new metaphor for human thinking, has (to a degree)
>copied at least one metaphor from third-generation computer science.
>

one of the things that has always amused me is that, to the extent that
I understand the structuring of computers, it seems that the cell
and the computer scientists have come up with similar solutions to
many of the same questions.  This is particularly true when one looks
at information flow in the cell.  I feel comfortable in assuming that
the cell had little help from the CS types in solving problems of information
flow.
It is likely to be true that contemporaries of in different scientific
fields play with each other's ideas.  This is why "Nature" insists on being so
broad and why F.H.C.C. can get work.

But I should stay more to the point.

>The Question or WHAT DO YOU THINK?
>----------------------------------
>Apparently, all human organ weights begin to decline shortly after puberty.
>The cumulative effect of this seeming reduction of resources isn't felt so
>strongly until middle-age, when we become more susceptible to disease.

>- Is mitosis sufficiently prone to failure to account for organ decline?
>
>I've heard that mammal cells appear to suffer a "hard" reproductive limit
>of 52 mitosis operations, and that meiosis "resets this counter" to 0.
>

It would seem to me that the step that is likely to give the cell trouble
is not mitosis but DNA replication.  If a whole chromosome lost or
non-disjoined, that cell is in some serious trouble.  Progressive
accumulation mistakes through replication and general maintanence seems a more
likely culprit.

I confess that once the topic turns to outside the single cell or involves
more than, say, two cells, I am hopelssly lost.
So the question of aging is outside my capabilities.  This will not, of course,
stop me from volenteering the following:
I have never liked the "hard-wired-number-of-mitosis" model.
I am not sure why; it just seems implausible, or worse yet, unecessary.
Supposedly "immortal" cells, like bacteria, actually have a rather high death
rate in the population (try doing a particle count then plating them out to see
how many are actually able to continue dividing).
Their apparent immortality is the result of unrestrained growth.
I suspect the failure rate is similar between bacteria and individual cells
of a metazoan.  The difference may be simply that a metazoan cannot tolerate
unrestrained growth of cell populations.  The cells are forced to stop
dividing when in contact with other cells.  they can be induced to re-enter
the cycle by growth factors released, for example, when the skin is cut.
I would guess that if one coupled the limitations on growth necessary to
be a metazoan with accumulated errors, both during replication and
simple maitanence, one could explain gradual breakdown of tissue without
invoking the "hard-wire" model.

oh well, I've gone on too long already.

tony (few degrees are worth remembering--and none are worth predicting)

Pelletier
Molecular etc. Bio
Boulder, Co. 80309-0347

P.S. I think alot about information flow problems and would enjoy
discussions on that...if anyone wants to chat.

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End of AIList Digest
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