Simply Complexity
by Neil Johnson
This is a book about the new science The Complexity Theory. This
new branch of science was a further development of the Chaos
Theory, but the emphasis has changed from examining the self
emergence of order from chaos to complex systems which follow
some mathematical models in explaining many emergent orders. The
book is not very academic and it uses some everyday examples such
as traffic jams, financial market crashes, wars and cancer growth
to demonstrate such systems.
A simple definition of the Complexity Science is the study of the
phenomena which emerge from a collection of interacting objects,
such as a crowd of people. For a more detailed definition, some
characteristics for such a system were identified.
First, there should be a population of multiple interacting agents
which typically forms a network. These agents may be very simple,
but not necessarily so. Second, there is competition or
cooperation among the agents for limited resources. Third, there
must be feedback processes which give the system memory and
history. With these characteristics, the agents are able to adapt
their strategies, and the system able to interact with its
environment.
A complex system is able to self-organize without the need of a central
controller, and there is emergence of non-trivial patterns of
behavior, including a complicated mixture of ordered and
disordered behavior.
The author gives many examples of complex systems, and a jazz band
is among the most interesting of these examples, where many
musicians interact with each others' playing and adjust their own
intuitively, leading to the emergence of a spontaneous new
performance every time. From the models he developed, It was
found that within a complex system, the population of agents will
often become polarized into two opposing groups. This tends to
reduce fluctuations in the behavior of the system. It is sometimes
possible to steer the behavior of a system by manipulating a
subset of the agents. The system is reinforced by networking and
its connectivity. Such models successfully demonstrate the
movement of stock markets, from a disordered market with bids and
offers cancelling each other, to sudden order leading to sharp
rise or fall owing to small disturbances. Traffic conditions
resulting from the complex interaction of individual drivers, and
tumour growth from the complex interaction of malignant cells
are the areas of research. It is hopeful that the research
results may give insight to more accurate prediction of the
behaviour of complex systems.
I try to link the group of Executive Officers to a complex
system. There are over 2,000 officers in the grade and they are
linked by information networks with frequent input and feedback.
There is a global network organized by the grade management, but
officers are also linked by many informal networks, some are
global and some are regional grouped by departments or past
colleagues. Sometimes this system displays disorder when officers
are going ahead with their own chores randomly. But sometimes
owing to some triggering information in the network, the system
can display some orders, or coordinated actions such as targeted
discussion on a topical subject, or even industrial action. Such
order may be discouraged through an inefficient centralized
information system. But in a complex system, agents will find a
way, or the shortest route, of information distribution.