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Ali, Tom and others,<br>
<br>
I agree with James Bednar's comments. Let me provide some more
intuitive reasons here so that more people on this list can
understand and see the point in the above title.<br>
<br>
Evolution is extremely important for the development of human body,
which is called morphogenesis at a lower level and only in a more
restricted sense (just shape). This is because the human body must
be developed (emerge) from a single cell (zygote). Different organs
in the body deal with very different functions. Limbs move; the
stomach digests; and the heart pumps blood. All these organs and
their functions must emerge from the single cell! The genome in
every cell beautifully regulates this process of body development.
This developmental process is largely still unknown, although a lot
of detail has been known in biology. <br>
<br>
The genome does not accomplish this miracle through
micro-management" (not just rigid "unfolding" organ structure).
Instead it regulates: The genome in each cell enables every cell to
work autonomously so that all emerged phenotypes successfully assist
the emergence of additional phenotypes through every cell's
experience! Designing the developmental program (DP) of the human
body is extremely difficult due to the high diversity of body organs
and their functions. There are some studies in theoretical
biology, physics and mathematics that discuss this process of
morphogenesis (just shape, not function though). In summary, the DP
for the body (e.g., mammals, primates, and human) are extremely
complex. Evolution for a body is interesting. However, since humans
can design a body and organs, as many engineered robots and organs
have shown). Evolution for a body is not comparable to engineered
bodies, as far as engineering is concerned. <br>
<br>
However, the same seems very different with the brain. A human
cannot handcraft a complex brain. One may argue: Similar to the
high diversity and complexity of body organs, the diversity and
complexity of the human brain are higher! David Touretzky along
many readers on this list would probably agree with this argument.
However, I think that this argument is not wrong, but superficial.
Why? Unlike a body which deals with various chemical molecules
(e.g., your food), a brain deals with mainly electric signals! Your
eye ball generates spikes; your ears generates spikes, your skin
generates spikes again. The effectors of the brain (muscles and
glands) are driven by spikes too. This is indeed a beauty of
nature. Therefore, the known knowledge in electrical system
modeling, such as those in mathematics, electrical engineering (EE),
and computer science (CS), are effective tools for us to understand
the brain-mind. A lot of theories, principles and tools have been
developed in the three disciplines that are essential for us to
understand the brain-mind. I am not saying that the current
knowledge in these three disciplines are sufficient, but I am saying
that the basic knowledge in these three disciplines are necessary if
one wants to scientifically understand brain-mind. <br>
<br>
From the above perspective, one can see why I can prove that the new
Developmental Network (DN) can abstract as well as any complex
Finite Automaton (FA) which is the basis model for all modern
symbolic models in artificial intelligence (AI). My recent article
titled "Why Have We Passed `Neural Networks Do not Reason Well'?"
will appear in the new INNS Society Magazine, Natural Intelligence.
It should be readable by everybody on this list. This paper bridges
the well known divide between symbolic networks (traditional AI) and
emergent networks (neural networks). <br>
<br>
Asim, it gives a detailed solution (with mathematical proofs under a
journal review) which implies that there is no brain neuron that
purely corresponds to an extra-body concept (e.g., the "Jennifer
Aniston" cell, the "Mother Teresa" cell, and the Pythagorean theorem
a^2 + b^2 = c^2 cell that Christof Koch talked about in <a
href="http://www.scientificamerican.com/article.cfm?id=being-john-malkovich">Scientific
American</a> 2011). The first theorem in my above paper indicates
that the brain network (modeled by GDN) does not need such concept
cells to learn any human society's knowledge modeled by a complex
FA, incrementally, immediately, and error-free. The other two
theorems indicate that GDN learning is optimal for noisy data. <br>
<br>
I guess that all on this list should be able to understand my above
paper, but not all will be able to understand my proofs without<br>
a solid background in CS, EE, and Mathematics. One cannot
understand what the above three theorems imply to brain-mind if he
or she has not learned biology, neuroscience, and psychology. Many
researchers doubt and said: "This is YOUR model". I asked back:
"What if it tells how the brain-mind works?" I did not ask: "Can
you afford to miss this opportunity by not starting to learn <br>
all the 6 discipline?"<br>
<br>
-John<br>
<br>
<br>
On 10/25/11 5:41 PM, Thomas Shultz, Dr. wrote:
<blockquote
cite="mid:1FF485229A413240911E654973965FC90282F0@exmbx2010-9.campus.MCGILL.CA"
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<div class="WordSection1">
<p class="MsoNormal"><span
style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">Ali
and John,<o:p></o:p></span></p>
<p class="MsoNormal"><span
style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span
style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">I
agree with Ali that we ignore evolution at our peril. It is
critically important that we come to understand how
evolution shapes the adaptability of organisms and how it
interacts with learning and development. All three of these
processes concern problems of adaptation, and they share
interesting algorithmic ideas and can even compensate for
each other. They are not in natural opposition as so many
psychologists assume. <o:p></o:p></span></p>
<p class="MsoNormal"><span
style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span
style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">I
also agree with John, and much of biology, that development
serves as a bridge between genotype and phenotype.
<o:p></o:p></span></p>
<p class="MsoNormal"><span
style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span
style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">Even
if one’s primary interest is in building human-inspired
robots, one should figure out what to build in, what to give
over to development, and what to leave to learning. Learning
methods themselves are products of evolution. We need to
understand all three adaptive processes, which occur on
different and nested time scales, and how they interact.
<o:p></o:p></span></p>
<p class="MsoNormal"><span
style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span
style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">Natural
evolution can indeed take a long time, but we can also study
its principles in computational models, much like we do with
cognition, development, and learning. <o:p></o:p></span></p>
<p class="MsoNormal"><span
style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span
style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">Cheers,<o:p></o:p></span></p>
<p class="MsoNormal"><span
style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">Tom<o:p></o:p></span></p>
<p class="MsoNormal"><span
style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<div>
<div style="border:none;border-top:solid #B5C4DF
1.0pt;padding:3.0pt 0in 0in 0in">
<p class="MsoNormal"><b><span
style="font-size:10.0pt;font-family:"Tahoma","sans-serif";color:windowtext">From:</span></b><span
style="font-size:10.0pt;font-family:"Tahoma","sans-serif";color:windowtext">
<a class="moz-txt-link-abbreviated" href="mailto:bmi-bounces@lists.cse.msu.edu">bmi-bounces@lists.cse.msu.edu</a>
[<a class="moz-txt-link-freetext" href="mailto:bmi-bounces@lists.cse.msu.edu">mailto:bmi-bounces@lists.cse.msu.edu</a>]
<b>On Behalf Of </b>Juyang Weng<br>
<b>Sent:</b> Sunday, October 23, 2011 8:14 PM<br>
<b>To:</b> <a class="moz-txt-link-abbreviated" href="mailto:bmi@lists.cse.msu.edu">bmi@lists.cse.msu.edu</a><br>
<b>Subject:</b> Re: [Bmi] BMI debate: Can we start to
look at the brain-mind from the entire system point of
view?<o:p></o:p></span></p>
</div>
</div>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Ali,<br>
<br>
Yes, from a scientific point of view, both development and
evolution are important to study. From an engineering point
of view, however, the cost of evolution to reach a human-level
performance is extremely high. Primates have a history of at
least 65 millions of years. <br>
<br>
This perspective does not rule out any possible benefits of
evolution in engineering studies. Partial evolution based on
development is still worth studying.
<br>
<br>
The major problem in many evolutionary models is the absence
of development --- genome is mistakenly taken to be task
specific, corresponding to intelligence directly. As I
understand, the main purpose of the genome is to regulate
development, not<br>
to directly generate behaviors or intelligence. <br>
<br>
-John<br>
<br>
On 10/20/11 3:02 PM, Ali Minai wrote: <o:p></o:p></p>
<p class="MsoNormal" style="margin-bottom:12.0pt">John<br>
<br>
I think that a developmental perspective is crucial if we're
ever going to understand how the mind emerges from the brain,
or how the brain-body system works. In fact, I would say that
we have to include not only development but also evolution -
not only how the zygote develops into a functional animal, but
also how simple animals evolve into animals with more complex
functionality by using the same modules in myriad ways. I have
argued (and am writing a book chapter on this) that the
"evo-devo" approach needs to be extended into the third
dimension of mental function - asking "what systematic
evolutionary and developmental processes allow the emergence
of a system capable of mental function. Just as we have the
idea of "evolvability", so there must be an equivalent idea of
"mentability" (or some such word) that distinguishes systems
capable of mental function from those incapable of this. This
should then be connected to development and evolution.<br>
<br>
All this said, I think that these types of global theoretical
approaches complement rather than replace the focused study of
specific subsystems like the hippocampus. Of course, I say
this as someone who has worked on such systems (including the
hippocampus, where Dave's work has been a major influence for
me). Both global and parcellated investigations contribute to
our understanding. To insist on one or the other would just be
an ideological choice.<br>
<br>
Best<br>
<br>
Ali<br>
<br>
<o:p></o:p></p>
<div>
<p class="MsoNormal">On Thu, Oct 20, 2011 at 2:07 PM, Juyang
Weng <<a moz-do-not-send="true"
href="mailto:weng@cse.msu.edu">weng@cse.msu.edu</a>>
wrote:<o:p></o:p></p>
<div>
<p class="MsoNormal">Dear all: <br>
<br>
After talking to some of my colleagues, we here kick of a
BMI debate via this email on
<a moz-do-not-send="true"
href="mailto:bmi@lists.cse.msu.edu" target="_blank">bmi@lists.cse.msu.edu</a>.<br>
Many of you on this anonymous list told me that they are
interested and want to be posted. However, we will use
this<br>
anonymous list sparely. If you want to keep posted about
this debate and other BMI activities, sign on bmi mailing
list
<br>
at <a moz-do-not-send="true"
href="http://lists.cse.msu.edu/cgi-bin/mailman/listinfo/bmi"
target="_blank">
http://lists.cse.msu.edu/cgi-bin/mailman/listinfo/bmi</a>
or simply Google it with key words like "BMI mailing list
MSU".<br>
Once you receive email from the mailing list, you can post
simply via reply. BMI mailing list is a moderated list
to avoid<br>
unrelated emails. If there are sufficient interest, BMI
might host a live web debate in a few weeks. Post your
views!<br>
<br>
The following email I sent to Dave Touretzky is the
kick-off for the BMI debates. I will provide some
interesting examples soon.<br>
<br>
On 10/20/11 12:59 PM, Juyang Weng wrote: <o:p></o:p></p>
<p class="MsoNormal">Hi Dave,<br>
<br>
I read some of your papers about hippocampus, which are
very interesting. Let me inject some basic but probably
very controversial ideas you probably will reject. If you
do not mind, I will post this discussion to the BMI
mailing list. The main purpose is to attract more
talented researchers to this important brain-mind
subject. <br>
<br>
How about looking at the brain from a top system point of
view? I believe that top (but detailed) theory is
powerful, since the brain basically does signal processing
(not in the traditional sense). Maybe with this view,
our future design of experiments could be more
productive? Let me start from one example:<br>
<br>
One of your papers is "Synaptic Learning Models of Map
Separation in the Hippocampus",
<i>Neurocomputing</i>, <b>32</b>:379-384, 2000. The
co-authors wrote: "If the perforant path projection to CA3
functions as a pattern completion mechanism, and the DG
projection via the mossy fibers performs pattern
separation (O'Reilly and McClelland, 1994), then ..."<br>
<br>
My new perspectives about the brain benefited from such
local views, but I think that such local views can also
benefit from the entire brain-mind point of view, in the
sense of a giant Finite Automaton (FA). This brain FA is
not handcrafted, but rather developed, since all
phenotypes emerge from a single cell (zygote). So, I
model such a developmental FA as the Developmental Network
(DN). Then, the Hippocampus is simply a very small part
of a giant DN. According to how the DN works, I predict
the following: If we focus on a small part (e.g.,
Hippocampus) of this DN, we definitely will get hopelessly
lost, like a hiker in a forest without a global map. He
can see some local phenomena from where he stands, but he
did not see the entire forest.
<br>
<br>
Focused, per-phenomenon discoveries have been prevailing
in the brain science literature in the modern science,
with few exceptions (Charles Darwin is one). This is
probably because only such papers can be accepted and
funded in the modern time. Although those phenomena are
useful, they are piece meals. Now, there seem to have
enough pieces to put the grand puzzle together. I have
established what a DN can do in real time, by modeling the
brain-mind from the entire FA (DN) point of view. Since
all pieces of DN seem to fit what we know about the brain
science, the brain should not be less efficient than a DN.<br>
<br>
You can say that this is just fantasy, but I have a series
of rigorous proofs. <br>
<br>
Daniel M. Wolpert said at SfN 2009 that the over 1400-page
long volume of "Principles of Neural Science" by Kandel et
al. could be much condensed if we could model the entire
brain in computational theory. I hope that the DN theory
can help that condensing process. <br>
<br>
A major infrastructure problem is that what I talked about
above spans at least 6 disciplines. Meaningful
conversations are extremely difficult. If you feel angry
or insulted by my above text, I feel that it is partially
because of this huge divide.
<br>
<br>
I am giving a CC to Jay, as his work was cited. <br>
<br>
Best regards,<br>
<br>
-John<o:p></o:p></p>
<p class="MsoNormal"><br>
-John<br>
<br>
<o:p></o:p></p>
<pre>-- <o:p></o:p></pre>
<pre>--<o:p></o:p></pre>
<pre>Juyang (John) Weng, Professor<o:p></o:p></pre>
<pre>Department of Computer Science and Engineering<o:p></o:p></pre>
<pre>MSU Cognitive Science Program and MSU Neuroscience Program<o:p></o:p></pre>
<pre>3115 Engineering Building<o:p></o:p></pre>
<pre>Michigan State University<o:p></o:p></pre>
<pre>East Lansing, MI 48824 USA<o:p></o:p></pre>
<pre>Tel: <a moz-do-not-send="true" href="tel:517-353-4388" target="_blank">517-353-4388</a><span style="color:#888888"><o:p></o:p></span></pre>
<pre><span style="color:#888888">Fax: <a moz-do-not-send="true" href="tel:517-432-1061" target="_blank">517-432-1061</a><o:p></o:p></span></pre>
<pre><span style="color:#888888">Email: <a moz-do-not-send="true" href="mailto:weng@cse.msu.edu" target="_blank">weng@cse.msu.edu</a><o:p></o:p></span></pre>
<pre><span style="color:#888888">URL: <a moz-do-not-send="true" href="http://www.cse.msu.edu/%7Eweng/" target="_blank">http://www.cse.msu.edu/~weng/</a><o:p></o:p></span></pre>
<pre><span style="color:#888888">----------------------------------------------<o:p></o:p></span></pre>
<pre><span style="color:#888888"><o:p> </o:p></span></pre>
</div>
</div>
<p class="MsoNormal"><br>
<br clear="all">
<br>
-- <br>
Ali A. Minai, Ph.D.<br>
Professor<br>
Complex Adaptive Systems Lab<br>
School of Electronic & Computing Systems<br>
University of Cincinnati<br>
Cincinnati, OH 45221-0030<br>
<br>
Phone: (513) 556-4783<br>
Fax: (513) 556-7326<br>
Email: <a moz-do-not-send="true"
href="mailto:Ali.Minai@uc.edu" target="_blank">Ali.Minai@uc.edu</a><br>
<a moz-do-not-send="true"
href="mailto:minaiaa@gmail.com" target="_blank">minaiaa@gmail.com</a><br>
<br>
WWW: <a moz-do-not-send="true"
href="http://www.ece.uc.edu/%7Eaminai/" target="_blank">http://www.ece.uc.edu/~aminai/</a><br>
<br>
<br>
<br>
<o:p></o:p></p>
<pre>_______________________________________________<o:p></o:p></pre>
<pre>BMI mailing list<o:p></o:p></pre>
<pre><a moz-do-not-send="true" href="mailto:BMI@lists.cse.msu.edu">BMI@lists.cse.msu.edu</a><o:p></o:p></pre>
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<pre>To subscribe or unsubscribe go to <o:p></o:p></pre>
<pre><o:p> </o:p></pre>
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<p class="MsoNormal"><br>
<br>
<o:p></o:p></p>
<pre>-- <o:p></o:p></pre>
<pre>--<o:p></o:p></pre>
<pre>Juyang (John) Weng, Professor<o:p></o:p></pre>
<pre>Department of Computer Science and Engineering<o:p></o:p></pre>
<pre>MSU Cognitive Science Program and MSU Neuroscience Program<o:p></o:p></pre>
<pre>3115 Engineering Building<o:p></o:p></pre>
<pre>Michigan State University<o:p></o:p></pre>
<pre>East Lansing, MI 48824 USA<o:p></o:p></pre>
<pre>Tel: 517-353-4388<o:p></o:p></pre>
<pre>Fax: 517-432-1061<o:p></o:p></pre>
<pre>Email: <a moz-do-not-send="true" href="mailto:weng@cse.msu.edu">weng@cse.msu.edu</a><o:p></o:p></pre>
<pre>URL: <a moz-do-not-send="true" href="http://www.cse.msu.edu/%7Eweng/">http://www.cse.msu.edu/~weng/</a><o:p></o:p></pre>
<pre>----------------------------------------------<o:p></o:p></pre>
<pre><o:p> </o:p></pre>
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and enter your e-mail address in the provided box and confirm your action by responding the the e-mail sent by listserv.</pre>
</blockquote>
<br>
<pre class="moz-signature" cols="72">--
--
Juyang (John) Weng, Professor
Department of Computer Science and Engineering
MSU Cognitive Science Program and MSU Neuroscience Program
3115 Engineering Building
Michigan State University
East Lansing, MI 48824 USA
Tel: 517-353-4388
Fax: 517-432-1061
Email: <a class="moz-txt-link-abbreviated" href="mailto:weng@cse.msu.edu">weng@cse.msu.edu</a>
URL: <a class="moz-txt-link-freetext" href="http://www.cse.msu.edu/~weng/">http://www.cse.msu.edu/~weng/</a>
----------------------------------------------
</pre>
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