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<div class="moz-cite-prefix">Dear John,<br>
<br>
Apologies for a delayed reply. I had a busy few days.<br>
<br>
I will gladly try answering your question on why your system using
a Markov decision process is a T2-system:<br>
<br>
Simply put, your system interacts with the environment at two
different levels:<br>
<br>
1) At one level, the system deals with the current states and the
decision of the next actions. At this level, the surrounding world
affects the system in the form of states that the system takes.<br>
<br>
In other words, a Markov process with fixed probability
distributions interacts with the world only at that one level and
thus, has one traverse and this is what makes it a T1.<br>
<br>
2) However, there is another important component of the
system--the learning mechanism for the probability distributions.
This part also interacts with the environment, but at a different
level of generality. This part estimates the probability
distributions from the past and therefore, makes the entire system
to interact with the environment also at a more general level.<br>
<br>
As a result, the system interacts, in total, at two levels with
its environment. And these two levels are organized into a
"poietic" hierarchy. The processes at one level (learning;
probability estimates) determine the properties of the other
(states to actions), but not the other way around (e.g., Markov
decision process does not act on its own learning rules, or on its
own probability distributions).<br>
<br>
These two levels of interaction make the system a T2. I think that
this is quite simple and does not require a formal mathematical
proof. I suggest reading the manuscript on practopoiesis to get
more insight.<br>
<br>
<br>
In general, all the intelligent algorithms that I know of, and all
of the brain theories that I know of, are based on T2-systems.
There is always one level that acts in response to sensory inputs,
and there is another level that is responsible for learning of how
to properly act (e.g., neural network + the plasticity mechanism).
<br>
<br>
In contrast to those theories, I argue that a biological organism
with a nervous system is in fact a T3-system. It has one more
(third) level of interaction with the environment, and all the
three levels are organized into a poietic hierarchy. This brings a
lot of additional flexibility, which a T2-system cannot achieve.
T3-systems are more adaptive than T-2 systems, much like
T2-systems are more adaptive than T1-systems. See here for some
accounts: <a class="moz-txt-link-freetext"
href="http://www.danko-nikolic.com/distinction-between-t2-and-t3-systems/">http://www.danko-nikolic.com/distinction-between-t2-and-t3-systems/</a><br>
Also, I argued that abductive reasoning can be achieved only by a
T3-system.<br>
<br>
To illustrate what a third adaptive level could bring to a Markov
process, imagine a system that can adaptively change its
probability matrices, from situation to situation, as needed--not
by representing the recent statistics of states, but by having a
large depository of probability functions (e.g., thousands) that
have been already acquired by some third mechanism and have been
extracted from a much broader sample of states (lifetime long).
Then, by looking at the history of the recent few states, the
system decides which of the probability functions it will use now
(which may be quite different than the recent statistics).<br>
<br>
This system would be a T3 because it would interact with the
environment at the following three levels:<br>
<br>
1) current state -> next action<br>
2) recent history of states -> choice of probability functions
from the depository<br>
3) long-term statistics -> creation of the probability function
depository<br>
<br>
Notice the strict poietic hierarchy among the three.<br>
<br>
I hope that this is clear enough and also enough of a teaser to
learn more about practopoietic theory.<br>
<br>
With best regards,<br>
<br>
Danko<br>
<br>
<br>
On 31/05/14 15:41, Juyang Weng wrote:<br>
</div>
<blockquote cite="mid:5389DBF1.4040409@cse.msu.edu" type="cite">
<meta content="text/html; charset=UTF-8" http-equiv="Content-Type">
<br>
<div class="moz-cite-prefix">On 5/30/14 5:01 PM, Danko Nikolic
wrote:<br>
</div>
<blockquote
cite="mid:9B96C174-C36D-4792-B15E-C0898C2DD382@gmail.com"
type="cite">
<div>Dear John,</div>
<div><br>
</div>
<div> I just read your SASE paper to make a comparison to
practopoiesis, as you asked. Interesting paper. Nice work.</div>
<div><br>
</div>
<div> I like your succinct stile, formal and accurate. Your
theorems make it clear what you mean by awareness, etc. </div>
<div><br>
</div>
<div> Here is what I can conclude about "A theory of
developmental architecture" by Juyang Weng: </div>
<div><br>
</div>
<div>Markov decision process is a T2-system. It does not make a
difference whether you have sensors that collect only outside
information or you also have sensors collecting internal
information. It remains a T2 system. The same holds for
actions. Internal actions do not change a T2 into T3 either.</div>
</blockquote>
Then, you must have rigorous and precise definition so that you
are not the only God to say T2 or T3.<br>
If your work is scientific, your detailed, rigorous and precise
definition but be able to be verified to be true or false by other
researchers.<br>
Otherwise, your work is religion like. <br>
<br>
For example, in the above your writing, you do not say "why" SASE
is T2 this is necessary for a scientific work.<br>
<br>
<blockquote
cite="mid:9B96C174-C36D-4792-B15E-C0898C2DD382@gmail.com"
type="cite">
<div><br>
</div>
<div> Therefore, according to practopoietic theory, your theory
falls into the category of T2-systems.</div>
</blockquote>
You do not seem to have a verifiable theory yet. It appears to
be religion like to me.<br>
<blockquote
cite="mid:9B96C174-C36D-4792-B15E-C0898C2DD382@gmail.com"
type="cite">
<div><br>
</div>
<div> As you know, I laid out arguments that this is not enough
to produce intelligent adaptive behavior that matches
biological behaving systems. My suggestion would be to find
ways to expand it into a T3.</div>
</blockquote>
Your arguments are too vague to be qualified as scientific work.
In religion, the God says "if you believe it, it is there.
Otherwise, it is not."<br>
<br>
-John<br>
<blockquote
cite="mid:9B96C174-C36D-4792-B15E-C0898C2DD382@gmail.com"
type="cite">
<div> </div>
<div>
<div>
<div>With best regards,</div>
</div>
</div>
<div><br>
</div>
<div><br>
</div>
<div>Danko</div>
<div><br>
</div>
<div><br>
</div>
<div><br>
</div>
<br>
<div>
<div>On May 28, 2014, at 2:30 PM, Juyang Weng wrote:</div>
<br class="Apple-interchange-newline">
<blockquote type="cite">
<div>Danko, thank you for the links. You might want to take
a look at my Self-Aware and Self-Effecting (SASE)<br>
architecture. Your three-traverse idea has some
similarity to it, but your theory is not (yet?) supported
by fully computational detail<br>
as SASE.<br>
<br>
-John<br>
<br>
On 5/28/14 6:58 PM, Danko Nikolic wrote:<br>
<blockquote type="cite">Dear all,<br>
</blockquote>
<blockquote type="cite"><br>
</blockquote>
<blockquote type="cite">I made an effort to make
practopoiesis more approachable to a wider audience:<br>
</blockquote>
<blockquote type="cite"><br>
</blockquote>
<blockquote type="cite"><br>
</blockquote>
<blockquote type="cite">One: I wrote a short popular
article on the implications of practopoiesis for
artificial intelligence:<br>
</blockquote>
<blockquote type="cite"><br>
</blockquote>
<blockquote type="cite"><a moz-do-not-send="true"
href="http://www.singularityweblog.com/practopoiesis/">http://www.singularityweblog.com/practopoiesis/</a><br>
</blockquote>
<blockquote type="cite"><br>
</blockquote>
<blockquote type="cite"><br>
</blockquote>
<blockquote type="cite"><br>
</blockquote>
<blockquote type="cite">Two: I made a list of the key
concepts with a brief explanation of each:<br>
</blockquote>
<blockquote type="cite"><br>
</blockquote>
<blockquote type="cite"><a moz-do-not-send="true"
href="http://www.danko-nikolic.com/practopoiesis#Concepts">http://www.danko-nikolic.com/practopoiesis#Concepts</a><br>
</blockquote>
<blockquote type="cite"><br>
</blockquote>
<blockquote type="cite"><br>
</blockquote>
<blockquote type="cite"><br>
</blockquote>
<blockquote type="cite">I hope that this will be helpful.<br>
</blockquote>
<blockquote type="cite"><br>
</blockquote>
<blockquote type="cite">With warm greetings from Germany,<br>
</blockquote>
<blockquote type="cite"><br>
</blockquote>
<blockquote type="cite">Danko Nikolic<br>
</blockquote>
<blockquote type="cite"><br>
</blockquote>
<blockquote type="cite"><br>
</blockquote>
<br>
-- <br>
--<br>
Juyang (John) Weng, Professor<br>
Department of Computer Science and Engineering<br>
MSU Cognitive Science Program and MSU Neuroscience Program<br>
428 S Shaw Ln Rm 3115<br>
Michigan State University<br>
East Lansing, MI 48824 USA<br>
Tel: 517-353-4388<br>
Fax: 517-432-1061<br>
Email: <a moz-do-not-send="true"
href="mailto:weng@cse.msu.edu">weng@cse.msu.edu</a><br>
URL: <a moz-do-not-send="true"
href="http://www.cse.msu.edu/%7Eweng/">http://www.cse.msu.edu/~weng/</a><br>
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<br>
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<pre class="moz-signature" cols="72">--
--
Juyang (John) Weng, Professor
Department of Computer Science and Engineering
MSU Cognitive Science Program and MSU Neuroscience Program
428 S Shaw Ln Rm 3115
Michigan State University
East Lansing, MI 48824 USA
Tel: 517-353-4388
Fax: 517-432-1061
Email: <a moz-do-not-send="true" class="moz-txt-link-abbreviated" href="mailto:weng@cse.msu.edu">weng@cse.msu.edu</a>
URL: <a moz-do-not-send="true" class="moz-txt-link-freetext" href="http://www.cse.msu.edu/%7Eweng/">http://www.cse.msu.edu/~weng/</a>
----------------------------------------------
</pre>
</blockquote>
<br>
<br>
<pre class="moz-signature" cols="72">--
Prof. Dr. Danko Nikolić
Web:
<a class="moz-txt-link-freetext" href="http://www.danko-nikolic.com">http://www.danko-nikolic.com</a>
Mail address 1:
Department of Neurophysiology
Max Planck Institut for Brain Research
Deutschordenstr. 46
60528 Frankfurt am Main
GERMANY
Mail address 2:
Frankfurt Institute for Advanced Studies
Wolfgang Goethe University
Ruth-Moufang-Str. 1
60433 Frankfurt am Main
GERMANY
----------------------------
Office: (..49-69) 96769-736
Lab: (..49-69) 96769-209
Fax: (..49-69) 96769-327
<a class="moz-txt-link-abbreviated" href="mailto:danko.nikolic@gmail.com">danko.nikolic@gmail.com</a>
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