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Complexity - Complex Systems Theory
Complex systems present problems both in mathematical modelling and philosophical foundations. The study of complex systems represents a new approach to science that investigates how relationships between parts give rise to the collective behaviors of a system and how the system interacts and forms relationships with its environment. The equations from which models of complex systems are developed generally derive from statistical physics, information theory and non-linear dynamics, and represent organized but unpredictable behaviors of natural systems that are considered fundamentally complex. wikipedia (en)
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Reflexivity, complexity, and the nature of social science

Reflexivity, complexity, and the nature of social science | Complexity - Complex Systems Theory | Scoop.it

In 1987, George Soros introduced his concepts of reflexivity and fallibility and has further developed and applied these concepts over subsequent decades. This paper attempts to build on Soros's framework, provide his concepts with a more precise definition, and put them in the context of recent thinking on complex adaptive systems. The paper proposes that systems can be classified along a ‘spectrum of complexity’ and that under specific conditions not only social systems but also natural and artificial systems can be considered ‘complex reflexive.’ The epistemological challenges associated with scientifically understanding a phenomenon stem not from whether its domain is social, natural, or artificial, but where it falls along this spectrum. Reflexive systems present particular challenges; however, evolutionary model-dependent realism provides a bridge between Soros and Popper and a potential path forward for economics.

 

 

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The reductionism stops here - Steve Keen

The reductionism stops here - Steve Keen | Complexity - Complex Systems Theory | Scoop.it

One of the defining features of neoclassical economics is the belief that macroeconomic analysis has to be not merely compatible with, but derivable from, microeconomic analysis. The development of economic theory has been driven far more by this belief than by the desire to make the theory compatible with the observed behaviour of the economy.

This ‘reductionist’ aspect of economics – the attempt to reduce the higher level topic of macroeconomics to an applied version of the lower level topic of microeconomics – is at odds with the last 50 years of genuine sciences, where complexity has ruled the roost, for reasons that were eloquently put by Physics Nobel Laureate Philip Anderson in a highly readable paper entitled “More Is Different”.

In that paper, Anderson asserted that reductionism did not work, because though it is possible to rank sciences in a hierarchy in which “The elementary entities of science X obey the laws of science Y, … this hierarchy does not imply that ‘science X is just applied Y’… At each stage entirely new laws, concepts, and generalisations are necessary, requiring inspiration and creativity to just as great a degree as in the previous one. Psychology is not applied biology, nor is biology applied chemistry.”

Economics violates this by its belief that “macroeconomics is just applied microeconomics”, but recent blogosphere debates have confirmed that there is a limit to how far neoclassical economists will take reductionism: it stops at microeconomics.

 

 

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