I came upon this free ebook, Complexity and Postmodernism by Paul Cilliers (Routledge 1998). From the introduction:
“Complexity and Postmodernism explores the notion of complexity in the light of contemporary perspectives from philosophy and science. Paul Cilliers contributes to our general understanding of complex systems, and explores the implications of complexity theory for our understanding of biological and social systems. Postmodern theory is reinterpreted in order to argue that a postmodern perspective does not necessarily imply relativism, but that it could also be viewed as a manifestation of an inherent sensitivity to complexity.
"As Cilliers explains, the characterisation of complexity revolves around analyses of the process of self-organisation and a rejection of traditional notions of representation. The model of language developed by Saussure—and expanded by Derrida—is used to develop the notion of distributed representation, which in turn is linked with distributed modelling techniques. Connectionism (implemented in neural networks) serves as an example of these techniques. Cilliers points out that this approach to complexity leads to models of complex systems that avoid the oversimplification that results from rulebased models.
"Complexity and Postmodernism integrates insights from complexity and computational theory with the philosophical position of thinkers like Derrida and Lyotard. Cilliers takes a critical stance towards the use of the analytical method as a tool to cope with complexity, and he rejects Searle’s superficial contribution to the debate.
"Complexity and Postmodernism is an exciting and an original book that should be read by anyone interested in gaining a fresh understanding of complexity, postmodernism and connectionism.”
And this from p. ix is indicative:
“It is necessary to say something about the relationship between complexity and chaos theory. The hype created by chaos theory has abated somewhat, but the perception that it has an important role to play in the study of complex systems is still widespread. Although I would not deny that chaos theory could contribute to the study of complexity, I do feel that its contribution would be extremely limited. When analysing complex systems, a sensitivity to initial conditions, for example, is not such an important issue. As a matter of fact, it is exactly the robust nature of complex systems, i.e. their capability to perform in the same way under different conditions, that ensures their survival. Although the metaphor of the butterfly’s flapping wings causing a tornado on the other side of the globe is a good one for describing a sensitivity to initial conditions, it has caused so much confusion that I feel it should not be used at all. Chaotic behaviour—in the technical sense of ‘deterministic chaos’—results from the non-linear interaction of a relatively small number of equations. In complex systems, however, there are always a huge number of interacting components. Despite the claims made about aspects of the functioning of the olfactory system, or of the heart in fibrillation, I am unsure whether any behaviour found in nature could be described as truly chaotic in the technical sense. Where sharp transitions between different states of a system are required, I find the notion of self-organised criticality (see Chapter 6) more appropriate than metaphors drawn from chaos. This might sound too dismissive, and I certainly do not want to claim that aspects of chaos theory (or fractal mathematics) cannot be used effectively in the process of modelling nature. My claim is rather that chaos theory, and especially the notions of deterministic chaos and universality, does not really help us to understand the dynamics of complex systems. That showpiece of fractal mathematics, the Mandelbrot set—sometimes referred to as the most complex mathematical object we know—is in the final analysis complicated, not complex. Within the framework of the present study, chaos theory is still part of the modern paradigm, and will not receive detailed attention.” (My emphasis.)
Note: This book admittedly explores the connectionist model. As I noted here in the Varela thread it pre-dates and does not include the enactivist model, which I prefer. Still, it has some important tales to tell.
Ongoing discussion at the IPS forum here.
“Complexity and Postmodernism explores the notion of complexity in the light of contemporary perspectives from philosophy and science. Paul Cilliers contributes to our general understanding of complex systems, and explores the implications of complexity theory for our understanding of biological and social systems. Postmodern theory is reinterpreted in order to argue that a postmodern perspective does not necessarily imply relativism, but that it could also be viewed as a manifestation of an inherent sensitivity to complexity.
"As Cilliers explains, the characterisation of complexity revolves around analyses of the process of self-organisation and a rejection of traditional notions of representation. The model of language developed by Saussure—and expanded by Derrida—is used to develop the notion of distributed representation, which in turn is linked with distributed modelling techniques. Connectionism (implemented in neural networks) serves as an example of these techniques. Cilliers points out that this approach to complexity leads to models of complex systems that avoid the oversimplification that results from rulebased models.
"Complexity and Postmodernism integrates insights from complexity and computational theory with the philosophical position of thinkers like Derrida and Lyotard. Cilliers takes a critical stance towards the use of the analytical method as a tool to cope with complexity, and he rejects Searle’s superficial contribution to the debate.
"Complexity and Postmodernism is an exciting and an original book that should be read by anyone interested in gaining a fresh understanding of complexity, postmodernism and connectionism.”
And this from p. ix is indicative:
“It is necessary to say something about the relationship between complexity and chaos theory. The hype created by chaos theory has abated somewhat, but the perception that it has an important role to play in the study of complex systems is still widespread. Although I would not deny that chaos theory could contribute to the study of complexity, I do feel that its contribution would be extremely limited. When analysing complex systems, a sensitivity to initial conditions, for example, is not such an important issue. As a matter of fact, it is exactly the robust nature of complex systems, i.e. their capability to perform in the same way under different conditions, that ensures their survival. Although the metaphor of the butterfly’s flapping wings causing a tornado on the other side of the globe is a good one for describing a sensitivity to initial conditions, it has caused so much confusion that I feel it should not be used at all. Chaotic behaviour—in the technical sense of ‘deterministic chaos’—results from the non-linear interaction of a relatively small number of equations. In complex systems, however, there are always a huge number of interacting components. Despite the claims made about aspects of the functioning of the olfactory system, or of the heart in fibrillation, I am unsure whether any behaviour found in nature could be described as truly chaotic in the technical sense. Where sharp transitions between different states of a system are required, I find the notion of self-organised criticality (see Chapter 6) more appropriate than metaphors drawn from chaos. This might sound too dismissive, and I certainly do not want to claim that aspects of chaos theory (or fractal mathematics) cannot be used effectively in the process of modelling nature. My claim is rather that chaos theory, and especially the notions of deterministic chaos and universality, does not really help us to understand the dynamics of complex systems. That showpiece of fractal mathematics, the Mandelbrot set—sometimes referred to as the most complex mathematical object we know—is in the final analysis complicated, not complex. Within the framework of the present study, chaos theory is still part of the modern paradigm, and will not receive detailed attention.” (My emphasis.)
Note: This book admittedly explores the connectionist model. As I noted here in the Varela thread it pre-dates and does not include the enactivist model, which I prefer. Still, it has some important tales to tell.
Ongoing discussion at the IPS forum here.
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