Modelling Mechanisms with Causal Cycles

Clarke, Brendan and Leuridan, Bert and Williamson, Jon (2014) Modelling Mechanisms with Causal Cycles. Synthese, 191 (8). pp. 1651-1681. ISSN 0039-7857. (doi:https://doi.org/10.1007/s11229-013-0360-7) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1007/s11229-013-0360-7

Abstract

Mechanistic philosophy of science views a large part of scientific activity as engaged in modelling mechanisms. While science textbooks tend to offer qualitative models of mechanisms, there is increasing demand for models from which one can draw quantitative predictions and explanations. Casini et al. (Theoria 26(1):5–33, 2011) put forward the Recursive Bayesian Networks (RBN) formalism as well suited to this end. The RBN formalism is an extension of the standard Bayesian net formalism, an extension that allows for modelling the hierarchical nature of mechanisms. Like the standard Bayesian net formalism, it models causal relationships using directed acyclic graphs. Given this appeal to acyclicity, causal cycles pose a prima facie problem for the RBN approach. This paper argues that the problem is a significant one given the ubiquity of causal cycles in mechanisms, but that the problem can be solved by combining two sorts of solution strategy in a judicious way.

Item Type: Article
Uncontrolled keywords: Bayesian nets Recursive Bayesian nets Cyclic causality Mechanisms Feedback Causal models Causation Mechanistic modelling
Subjects: B Philosophy. Psychology. Religion > B Philosophy (General)
B Philosophy. Psychology. Religion > BC Logic
Divisions: Faculties > Humanities > School of European Culture and Languages > Philosophy
Depositing User: Jon Williamson
Date Deposited: 16 Jun 2014 16:18 UTC
Last Modified: 15 Jun 2015 14:06 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/41455 (The current URI for this page, for reference purposes)
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