On Paul Cilliers’ Approach to Complexity:Post-structuralism versus Model Exclusivity

Abstract

Paul Cilliers has developed a novel post-structural approach to complexity that has influenced several writers contributing to the current complexity literature. Concomitantly however, Cilliers advocates for modelling complex systems using connectionist neural networks (rather than analytic, rule-based models). In this article, I argue that it is dilemmic to simultaneously hold these two positions. Cilliers' post-structural interpretation of complexity states that models of complex systems are always contextual and provisional; there is no exclusive model of complex systems. This sentiment however appears at odds with Cilliers' promotion of connectionist neural networks as the best way to model complex systems. The lesson is that those who currently follow Cilliers' post-structural approach to complexity cannot also develop a preferred model of complex systems, and those who currently advocate for some preferred model of complex systems cannot adopt the post-structural approach to complexity without giving up the purported objectivity and/or superiority of their preferred model.

How pluralistic is pluralism really? A case study of Sandra Mitchell’s Integrative Pluralism

“…Although my target is IP, my argument may carry implications for other epistemological pluralists working in the philosophy of science. Naturally, a pluralistic thesis should be logically and axiologically consistent with the principles of pluralism (see van der Merwe, 2021). Philosophers disagree about many things, including foundational suppositions.…”