Complexity Explained - P. Erdi (Springer, 2008) WW.pdf

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Peter Erdi
Complexity Explained
Peter Erdi
Complexity Explained
With 129 Figures
123
Péter Érdi
Kalamazoo College
Center for Complex Systems Studies
Department of Physics, Department of Psychology
Academy Street 1200
49006 Kalamazoo
USA
perdi@kzoo.edu
and
KFKI Research Institute for Particle and Nuclear Physics
Hungarian Academy of Sciences
Department of Biophysics
Konkoly-Thege út 29–33
1121 Budapest
Hungary
erdi@rmki.kfki.hu
ISBN-13 978-3-540-35777-3
e-ISBN-13 978-3-540-35778-0
DOI 10.1007/978-3-540-35778-0
Library of Congress Control Number: 2007934800
c
2008 Springer-Verlag Berlin Heidelberg
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Cover design: Erich Kirchner, Heidelberg
Printed on acid-free paper SPIN 11545286 89/3180/YL
987654321
springer.com
To the memory of my parents
Preface
This book is, of course about complexity. The title of the book, as you may
recognize was motivated (excuse me for using this very mild expression) by
Daniel Dennett’s Consciousness Explained [130]. Dennett’s intention was to
explain consciousness as the emergent product of the interaction among con-
stituents having physical and neural character. The goal of this book is to
explain how various types of complexity emerge due to the interaction among
constituents. There are many questions to be answered, how to understand,
control, decompose, manage, predict the many-faced complexity. After teach-
ing this subject for several years I feel that the time has come to put the whole
story together.
The term “complex system” is a buzzword, but we certainly don’t have
a single definition for it. There are several predominant features of complex-
ity. Complex processes may show unpredictable behavior (which we still try
to predict somehow), may lead to uncontrolled explosion (such in case of
epilepsy, earthquake eruptions or stock market crashes). One of the charac-
teristic feature of simple systems is, that there is a single cause which implies
a single effect. For large class of complex systems it is true that effects are
fed back to modify causes. Biological cells belong to this class. Furthermore
they are open to material, energetic and information flow by interaction with
their environment, still they are organizationally closed units. Another aspect
of complexity is the question how collective phenomena emerge by some self-
organized mechanisms. Thomas Schelling’s model, which suggests that strong
racial prejudice is not needed to generate urban segregation, is paradigmatic.
There is a remarkable and unique statistical feature of certain complex
systems. Generally we expect that there is an average, (say, the average height
of people), and the deviation from this average is symmetric. Biologists have
found that the Gaussian distribution can be applied in many, many cases. In
a large number of social systems (but not only there) we see another type
of pattern, occasionally called as the 80 / 20 rule. About 80 percent of the
income is made by 20% of people, 80% (well, 70 or 85) of flights are landing
on twenty percent of the airports, while there are many small airports with
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