The study of complexity has emerged out of a number of analytical trends in the physical and biological sciences in the last century, principally in the fields of computing and computer modelling, cybernetics, dynamical system theory (a branch of classical mechanics which studies the properties and interactions of many-bodied point mass systems), 'organismic' biology (an approach to theoretical biology emphasizing an analytic approach to vitalistic concepts such as teleology) and thermodynamics. In an attempt to provide modern scientific foundations for vitalistic notions such as teleological behaviour, analytic biologists such as Cannon and Sommerhoff proposed analytic or behavioural analyses and definitions of biological notions. Once given a behavioural grounding, these models were able to migrate out of biology, to account for analogical features of non-biological systems: first to the study of machines and control systems in cybernetics, and thence to a wide range of physical and social processes, aided by developments in non-linear dynamics such as dynamical systems theory, the emergence of the statistical sciences, and the development of modern computer modelling. Somewhat surprisingly, there has been little theoretical interaction between complexity theory and continuum mechanics, a part of classical mechanics that also deals with non-linear phenomena (such as elastic collisions or fluid flow), perhaps because complexity theory standardly deals with systems of discrete elements, and not homogenous continua. A consequence is that non-linearity may not be a sufficient characterization of complexity. ‘Complexity’ (a term that can describe behaviour and function equally well as structure) has since become a trans-disciplinary umbrella term that is intended to denote that feature of entities which is claimed to be responsible or to account for such characteristics, in both living and non-living systems. Complexity, as a concept, thereby provides not only analysis, but also (and perhaps more crucially, yet contentiously) a uniform explanation for the structure and behaviour of a very extensive range of phenomena. Philosophical problems associated with complexity include clarifying the meanings of various concepts associated with complexity, such as emergence, non-linearity, feedback, adaptation, and self-organization, and the extent to which these terms can be given scientific meaning, that is, the extent to which these terms can be meaningfully used in the physical sciences themselves. The study of complexity also naturally intersects with more traditional problem areas in the philosophy of the sciences, such as the study of reductionism, modelling, supervenience, functionalism, and causality; however the focus of contemporary philosophy of complexity has largely tended towards the examination of (or in many cases, an attempt at the legitimization of) a scientific grounding of a particular set of approaches to these problem areas. Much of this focus is surely due to the fact that the study of complexity in the twentieth century has largely been driven by scientific practitioners themselves, and not by philosophers or philosophers of science. As such, contemporary complexity theory also makes assumptions about the relationship between scientific and philosophical theories, leading to one of its central problems: its essential ambiguity. Is complexity science a specific branch of physical science (for example, the study of 'complex adaptive systems'); a study of a widespread trans-disciplinary scientific phenomenon (leading to the study of, for example, various broad 'measures of complexity', not to speak of complexity in other divisions of science, including biological and social complexity); or even a general (and allegedly paradigmatic) approach to science itself (the source of many popularizations, and in some cases works bordering on pseudo-science)? This ambiguity (which is reflected in the bibliography) opens up further avenues for exploration, and has implications for the manner in which philosophers should attempt to approach the subject.
|Key works||Weaver 1948, Simon 1962, and Ashby 1962 are classic early works, generalizing concepts from cybernetics. Buckley 1968 is an early application to sociology and is likely the origin of the concept of a 'Complex Adaptive System', later explored in Holland 1992. Prigogine 1984 explores a model of complexity based on ideas from thermodynamics; Various proposed measures of complexity are explored in Bennett 1988, Lloyd & Pagels 1988 and Gell-Mann 1995. Kauffman 1969 and Bak 1996 are the origins of the influential models of Random Boolean Networks and Self-Organized Criticality, respectively.|
|Introductions||A comprehensive introduction to many of the technical and philosophical issues of complexity can be found in Ladyman et al 2013. Book-length introductions to the diverse areas of research in complexity are Mitchell 2009 and Hooker 2011. Historical context is provided in Abraham 2011 and Francois 1999, as well as Keller 2008 and Keller 2009. There is a paucity of discussion of the subject in a manner that would be familiar to academic philosophers; in addition to Ladyman et al 2013, readers can consult Phelan 2001, Frigg 2003, Poser 2007, Taborsky 2014, and Zuchowski 2018.|
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David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
Darrell P. Rowbottom
Aness Kim Webster
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