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Self-organizing systems. A manifesto of sorts
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I have been working on a theory of the functioning of self-organizing systems (hereunder  
SoS) for over 30 years.  My research concerns the following problems.

(A) A theory of behavior of self-organizing systems, including the character
of response of an entire system to an impact of the environment, as well as
to various intra-system changes caused by external intrusions into the system.


We have determined that a SoS cannot consist of identical elements interacting in an identical
way, which has led us to development of a technique based on the following principle: if you
add to a SoS multiple copies of one of its elements, then, starting from a certain number of
the added copies, the original element along with its copies will lose its functional connection
with the system. This phenomenon can be used for assessment of the strength of connection
between the system and any of it individual elements.  

We have proposed the information ego-entropy criterion that allows for investigation of the fine
structure of domain walls within a SoS as well as its exterior wall.  We have demonstrated that
the piercing of a SoS by an individual element reveals important peculiarities of the SoS
structure and, in particular, allows for observation of high-frequency oscillations of the domain wall
which occurs in a domain that contains a smaller domain, whose domain wall does not touch the
domain wall of the larger domain.  

We have demonstrated the use of these techniques in quantitative analysis of global demographic
data (the year 2000 population pyramids for 220 countries), and as a methodological platform for
evaluation of certain trends in the behavior of natural SoS. 

Specifics of the behavior of SoS which follow from the above-provided definition of SoS and from
the knowledge acquired through computer-aided imitation of the SoS behavior were taken into
account in the theory of the origin of life on Earth that I have formulated and published. My theory
is based on the fact of the capability of lipid micelles to participate in the transformation of Mg
ions to MgO, thus concentrating energy noises into a molecular transmitter of energy, i.e. an ATP
precursor. As the prebiotic Earth had no atmosphere, meteorite falls to Earth were causing
high-level oscillations in wide ranges of frequencies. Breakdown of magnesium salts of enolforms
of lipids resulted in production of magnesium oxide which initially was bonding mainly

with phosphates (pyrophosphate and polyphosphates) and in the course of the evolution became
a part of ATP. Upon interaction with water, magnesium oxide releases 12 Kcal/mol, i.e. the
same amount of energy that ATP produces upon biochemical transformations. Thus,
spontaneous synthesis of magnesium oxide and, subsequently, of ATP was the starting point
in the origination and evolution of life on Earth. ATPase that synthesizes ATP in modern
organisms represents an autonomous SoS whose functioning is based on principally the same
foundation as the prebiotic systems of synthesis of MgO from Mg ions.      

 
(B) Specifics of the theory of complexity as applied to SoS.

We have demonstrated that any SoS has a domain structure; that any SoS represents an
interaction between  chaos of the order and chaos of disorder; that Schrodinger’s principle
of negentropy explains peculiarities of behavior of the stable complexity of SoS; and that
inter-domain walls have a three-layer structure.


(C) Computer simulation of the functioning of SoS, including various novel,
heretofore unavailable, computer techniques and their practical applications.

We have developed a technique based on the use of a drifter element which allows for
computation of the aura of any SoS. One of our patented methods provides an “infothyristor”
technique that allows for recognition of object distributions involving practically unlimited
numbers of objects and parameters.

A self-organizing system, in my understanding, is such a complex of elements which, in the
absence of a control center, can display, on a spontaneous basis, a structural-functional
activity in the form of a cooperative response to both exogenous impacts and to changes in
the current intra-system status of any of the elements of the system. A self-organizing system
has an aura that represents a multi-dimensional space of parameters where any individual
element, being outside the system but within its aura, experiences the effect of processes
that occur in the system.  This definition well agrees with the concept of SoS as a “black box”
according to Norbert Wiener.


The term ‘system’ has an extremely wide usage both in science and everyday life, which
often causes confusion as to what a particular author may imply when using the term. When
we speak of ‘education system’, or ‘system of punishments’, etc., we mean something that
has nothing to do with SoS. And there is a great number of systems that perfectly fit the
above-given definition of SoS and whose principles of functioning are extremely important
for understanding by the mankind: e.g. the Universe, atoms, economy, global social system,
intelligence, climate, ecology, tectonic processes, and many others.

In accordance with the above-provided definition of SoS, systems that surround us, or
constitute us, and are of importance to us can be classified in various ways depending on
practical and theoretical requirements to such classification. For instance, of all the known
SoS the human mind is the only system that is capable of the studying of itself. There are
systems that cannot be subjected to human impact -- e.g. the Universe. Human impact on
the Universe is negligibly small. However, humans have found ways to handle atoms and
molecules by using atomic energy in their interest. Humans are making tremendous efforts
trying to gain control over the system that is called economy which nonetheless stays
control-resistant. Research into any area of SoS activity -- e.g. the weather, demography,
sociology, ethnopsychology, ecology, etc. -- requires not only specific methods of holistic
investigation but also the development of a general theory of functioning of SoS.

Classic science whose laws and conclusions are used by modern humankind in its
practical activities is based on reductionism as the only practically available
methodological approach. However, the study of SoS is impossible without holistic
methodology, which does not yet exist as a research tool. Aristotle's thesis that a whole
is bigger than the sum of its parts can serve as a touchstone for scientific approaches to
investigation of complex natural and social systems. The development of theoretical
grounds for computer-aided imitation of SoS behavior and their practical implementation
in the form of software capable of simulation SoS behavior is a problem that is both
tremendously complex and crucially important for the modern science. 

The main obstacle lies not just in the fact that additivity in general is not inherent in SoS,
but in the fact that practically all of the known mathematical methods have only limited
application in studies of highly complex natural phenomena and are completely useless
for the purpose of description of behavior of native SoS in general. Once widely
popularized, synergetics is merely an imitation of science on the behavior of SoS.
However, these problems have been largely ignored as they are pointing at the necessity
of drastic revision of many of the fundamental principles of the modern classic science,
which would be against the interests of the majority of people directly or indirectly
involved in science and research.     


A couple of decades ago, it seemed as if the solution of all the problems lies in the
computer processing power. That illusion was caused by naive unwillingness to
acknowledge the apparent impasse on the route of using classic scientific approaches.
A significant part of the supercomputing resources that were created and acquired in
anticipation of unlimited potentials provided by the unlimited computing power is not
scientifically productive. The increase of the supercomputer speed does not equate to,
for instance, increase of the accuracy of the weather forecast as the weather is an
expressly self-organizing system.

The idea of centralized collection of information from a large number of sources and
processing
it by using the world's most powerful supercomputers for the purpose of
prediction of social trends and economic crises cannot be viable in the absence of
fundamental knowledge on the behavior of SoS in general.

The possibility of analysis of fragments of SoS and the capability to make an impact
on particular SoS are not an indication that, when reproduced, the same analyses
and same impacts will not provide different or opposite results. This simple truth is
evident, for instance, from the historic and current state of the science of economics
where the views of many of the Nobel prize economists on the mechanism of
functioning of the economy are diametrically opposite to each other or incompatible
with each other. 

Over 30 years ago, I developed an algorithm of the evolutionary transformation of
similarity matrices (ETSM). The ETSM algorithm and the methods and techniques
based on the algorithm and disclosed by me in three U.S. Patents provide a capability
for imitation of SoS behavior. About 15 years ago, the ETSM-based technology was
implemented, under my leadership, in a computer program, "MeaningFinder",
providing for simulation of SoS behavior, i.e. opening the road for the practical use
of the methodology of holism.      
 
"MeaningFinder" is the key method used in my investigations. It allows for analysis
of systems with large numbers of objects described by unlimited numbers of
parameters. In computation of similarity matrices, the program alternately uses
two patented metrics: one is for parameters that reflect "power" of the objects, and
another for parameters that reflect "shape" of the objects. A similarity matrix for
a set of objects under analysis is created by hybridization of the so-called monomer
similarity matrices computed by each parameter individually, which allows for
processing of an indefinitely large number of parameters.

The resulting hybridized and dimensionless similarity matrix is then subjected to
successive transformations that result in for the averaging of all of the similarity
coefficients for each of the objects under analysis. As a result of this perfectly
objective process that in no way is influenced by the will of the program
developer or the data analyst, the objects under analysis are automatically
divided into two groups, with no outliers.

This unique process of bifurcation resulting from the averaging of similarity
matrices for a set of objects provides the basis for automated hierarchical data
clustering reflecting the relations between the elements of a SoS. The
ETSM-enabled bifurcation with no outliers successfully occurs even systems
including elements with randomized parameter values, i.e. the algorithm has
universal application in data processing. 

The behavior of the biosphere in general and the noosphere in particular
(in the meaning of the 'sphere of the human thought') seems to have the SoS
behavior pattern: they do not have a control center and they function based
on polymodal spontaneous interactions between their constituent entities.
Therefore, the methods and approaches developed by me can be organically
incorporated in the FuturICT project. The MeaningFinder software would be
especially beneficial for the project as its architecture and algorithmic concept
provide for handling unlimited numbers of parameters describing the objects
under analysis.


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