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Modelling mechanisms with causal cycles

Clarke, B; Leuridan, B; Williamson, J; (2014) Modelling mechanisms with causal cycles. Synthese , 191 (8) pp. 1651-1681. 10.1007/s11229-013-0360-7. Green open access

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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.

Type: Article
Title: Modelling mechanisms with causal cycles
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/s11229-013-0360-7
Publisher version: http://dx.doi.org/10.1007/s11229-013-0360-7
Language: English
Additional information: The final publication is available at Springer via http://dx.doi.org/10.1007/s11229-013-0360-7.
Keywords: Bayesian nets, Recursive Bayesian nets, Cyclic causality, Mechanisms, Feedback, Causal models, Causation, Mechanistic modelling
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Science and Technology Studies
URI: https://discovery.ucl.ac.uk/id/eprint/1536352
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