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3.5 Underlying Theories and the Natural World
If the model cannot be pre-de
ned, then it needs to be learned. To do this, the
computer program needs to be given a set of rules to use as part of the construction
process. For a generic solution, these rule sets are usually quite simplistic in nature.
Again taken from Greer (
2008
, Chap. 1), Complex Adaptive Systems is a general
term that would also comprise the sciences of bio-inspired computing. The term
Complex Adaptive Systems (or complexity science), is often used to describe the
loosely organised academic
field that has grown up around the study of such
systems. Complexity science encompasses more than one theoretical framework
and is highly interdisciplinary, seeking the answers to some fundamental questions
about living, adaptable and changeable systems. A Complex Adaptive System (for
example, Holland
1995
; Kauffman
1993
) is a collection of self-similar agents
interacting with each other. They are complex in that they are diverse and made up
of multiple interconnected elements and adaptive in that they have the capacity to
change and learn from experience. One de
nition of CAS by Holland (
1995
), one
of the founders of this science, can also be found in Waldrop (
1993
) and is as
follows:
A Complex Adaptive System (CAS) is a dynamic network of many agents (which may
represent cells, species, individuals, firms, nations) acting in parallel, constantly acting and
reacting to what the other agents are doing. The control of a CAS tends to be highly
dispersed and decentralised. If there is to be any coherent behaviour in the system, it has to
arise from competition and cooperation among the agents themselves. The overall
behaviour of the system is the result of a huge number of decisions made every moment by
many individual agents.
The nature of the interactions between the individual entities is the key aspect
that distinguishes such complex systems from complicated systems (Al-Obasiat and
Braun
2007
). A system is called complex if the interactions between its components
are not predictable and if it has at least one or more of the following characteristics:
It is non-linear.
It is dynamic.
It is time-variant.
It is chaotic or stochastic.
All telecommunication networks possess one or more of these attributes.
Complicated systems are an alternative type of complex system. However, while
complicated systems interact in a predictable way, with CAS, the unpredictable
interactions between individual components in the system give rise to
'
behaviour. Emergence is the process of complex pattern formation from simpler
rules. An emergent behaviour arises at the global or system level and cannot be
predicted or deduced from observing the behaviour of the individual components in
the lower-level entities. Because of external forces, concept trees would probably be
classi
'
emergent
ed as complex, because their construction is unpredictable.
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