Complexity science may be described as a set of principles for analyzing and understanding complex adaptive systems. These principles encompass elements of several other schools of thought including Adaptation & Evolution, Network Theory, Systems Theory, Self-Organization, and Nonlinear Systems.
Some key elements of complexity science are:
Complex adaptive systems are continuously evolving and changing networks of adaptive agents.
Adaptive agents engage in communication and exchange and continuously adapt to new, mutually-created conditions and challenges.
Examples of complex adaptive systems include individuals in social groups, investors in capital markets, consumers and businesses in the economy, species in food webs, and populations of cities.
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Complexity science suggests the economy and markets may be analyzed as complex adaptive systems that are continuously changing and adapting to new, mutually-created conditions. It’s a unique, real-world view, and contrasts with many standard economic and investing frameworks that rely on rigid and often unrealistic assumptions.