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Thank you, Marvin, for this suggestion. I typically do as you. I
guess that this pre-publication case one should be fine too as IEEE
TAMD has already put pre-publication versions on its IEEE Explore
web. The new link is below:<br>
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<font color="#000000"><br>
J. Weng, "Symbolic Models and Emergent Models: A Review," <i>IEEE
Transactions on Autonomous Mental Development</i>, accepted and
to appear in vol. 4, 2012. <a
href="http://www.cse.msu.edu/%7Eweng/research/SymbEmerg-Weng-TAMD-2011-IEEEprepub.pdf">PDF
file</a>.<br>
<br>
More detail about how network emergent representations are without
any rigid module for extra-body concepts but can abstract well is
available at:<br>
<br>
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<font color="#000000">J. Weng, "Why Have We Passed `Neural Networks
Do not Abstract Well'?'', <em>Natural Intelligence: the INNS
Magazine</em>, vol. 1, no.1, pp. 13-22, 2011. <a
href="http://www.cse.msu.edu/%7eweng/research/WhyPass-Weng-NI-2011.pdf">PDF
file</a></font><br>
<br>
Please air your objections to this list, as they are very important
for many others to critically think. <br>
<br>
Yes, I have many many cases where groups get better ideas than its
individuals. Laws for human groups and programs for AI agents all
have a long way to go compared with the beautiful ways that the
brain generates group intelligence from <br>
100 billion autonomous cells! <br>
<br>
For human groups: <br>
<br>
(1) China: the first 30 years after 1949. The nation's learning
program (Developmental Program (DP), or constitution first, then
laws, and next regulations) was so badly designed that group
intelligence in China was among the worst in the world, even worse
than the current North Korea. The Chinese constitution that time
was like symbolic representations in AI. It stipulates a static
structure of intelligence --- socialism was the doctrine of the
nation, static! It stipulated that Zhedong Mao is the leader, a
central controller of the country's "brain". Mao had very limited
knowledge about scientific ways to run a country. He did not even
know about market economy!<br>
<br>
(2) China: the second 30 years after 1949. I used the same country
as my example so that other factors are more or less similar. The
current DP of China, since Xiaoping Deng came to power after Zhedong
Mao's death in the middle 1970's, was also very badly designed.
Group intelligence in China was still among the worst in the world.
The current Chinese Constitution still stipulates that a single
party is the leading party. It is still like symbolic
representation, static in terms of a small module in power. But
within the party, used to be one person who made all decisions, now
a few people in political bureau make all the major decisions. Only
this slight change of DP, mainly made by Xiaoping Deng, introduced
some dynamics into DP. Due to this little emergent representation
about group intelligence, China moved its Per Capita PPP (Purchasing
Power Parity) GDP to around 99 in the world in 2010. With its large
population, this bad number moved China to No. 2 in total GDP.<br>
<br>
(3) US: I leave this subject to free discussion, because I will meet
more objections. All the major problems in US, as far as I can see,
are due to the systematic rigidity of the US DP currently in
place. I wish that US Congress and Senate would come to the
Brain-Mind Institute from the summer 2012 to learn how the group
intelligence works in the brain. But I understand this is hard
until US public can see that their coming will fundamentally solve
all the major problems in US and in the world. Subprime crisis in
2008? Occupying the Wall Street in 2011? An obvious lack of
knowledge about group intelligence.<br>
<br>
For machine groups:<br>
<br>
(1) Each machine individual: We need brain-like DP to run our
developmental robots. This is a new era that few can see now. I
humbly estimate that all major bottleneck problems of AI have been
solved by DN in an integrated way, at least in theory with some
exciting experimental results. Demonstration of human-level
performance by machines will take a little more time, as it requires
money. Is there any chance for a symbolic machine to solve major
bottleneck AI problems? Almost none. Sorry to say. However, it is
easier for symbolic representations to get funded. <br>
<br>
(2) Group intelligence in AI: The future societies consisting of
wetware humans and hardware robots will need to go through<br>
the similar periods that the human societies went through in the
last 250 years. However, the speed of progress will be much
faster, since the 6 disciplines have accumulated much more facts and
knowledge about group intelligence than 250 years ago.<br>
The current delay in due progress is mainly due to the cost of
communication (what we are doing now), instead of due to a lack of
facts and knowledge. The cost of communication in China is even
higher, as the Brain-Mind Workshop that we are trying to run now at
Fudan University in Shanghai has shown. Researchers in China do
not believe that brain works this way computationally, almost like
researchers in developed countries as indicated by the respected
reviewers who reviewed my above IEEE TAMD paper. <br>
<br>
By the way, my proof of DN-FA relationship was submitted to the
journal you knew, but it was rejected even after I mentioned your
name with a CC to you. The first rejection came without any review;
the second rejection came with only a single-person 1-paragraph
review.<br>
<br>
-John<br>
<br>
On 12/16/11 4:58 AM, Marvin Minsky wrote:
<blockquote
cite="mid:F0DB0206-E85F-4355-8069-1B8464AD494C@gmail.com"
type="cite">
<pre wrap="">You would probably win your bet -- except that many people cannot access your paper -- because you didn't include the text. So I have no idea what you are talking about, and I don't want to pay a journal for it.
I put my papers on my home page, and do not give exclusive copyrights to journals.
Do you know many cases where groups get better ideas than its individuals? For which kinds of problems does that happen?
On Dec 15, 2011, at 1:12 PM, Juyang Weng <a class="moz-txt-link-rfc2396E" href="mailto:weng@cse.msu.edu"><weng@cse.msu.edu></a> wrote:
</pre>
<blockquote type="cite">
<pre wrap="">I bet that many people on this mailing list are against the views expressed
in my paper.
</pre>
</blockquote>
</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>
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