I don’t believe in the existence of a complex systems theory as such and, so
far, I’m still referring to complex systems science (CSS) in order to describe
my research endeavours. In my view, the latter is constituted, up until now,
by a bundle of loosely connected methods and theories aiming to observe—
from contrasted standpoints—these fascinating objects of research called
complex adaptive systems. Nearly 40 years after Von Bertalanffy’s General
System Theory (1968) and Jacques Monod’s Chance and Necessity (1971),
it is fair to look back and to try to assess how much remains to be said about
these complex adaptive systems. After all, Prigogine’s Order out of Chaos
(1984) already demonstrated that future wasn’t entirely predictable in a history-
contingent world. Nearly at the same period, Maturana and Varela’s
Tree of Knowledge (1987) questioned the closure of biological systems and
proposed a challenging theory of autopoieitic systems, oddly left aside by
CSS’s mainstream research. Later on, Holland’s Hidden Order (1996) set out
the terminology associated with and the characteristics of complex adaptive
systems, still in use nowadays. More recently, Watts’s Six Degrees (2004)
epitomized current assumptions of network theorists asserting that a system’s
structure and organization—most of the time—dictate its functional properties.
What remains from these influential contributions are a heterogeneous
corpus of partly conflicting theories and a disparate set of tools and methods.
Furthermore, too often complex systems science lends itself to criticism when
it trades its artificial complex adaptive systems for natural (i.e., actual) ones.
The universe is a massive system of systems -- for example, ecological systems, social systems, commodity and stock markets. These systems are complex, constantly adapting to their environment, and many are essential to the very existence of human beings. To fully understand these systems, complex adaptive systems research uses systemic inquiry to build multi-level and multidisciplinary representations of reality to study these systems.
Applications of Complex Adaptive Systems provides a global view of the most up-to-date research on the strategies, applications, practice, and implications of complex adaptive systems, to better understand the various critical systems that surround human life. Researchers working in the field of complex adaptive systems and related fields such as machine learning and artificial intelligence, multi-agent systems, and data mining, as well as professionals in related applications such as defense, bioinformatics, and sociology will find this book an indispensable, state-of-the-art reference.