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A Modeling Approach for Mechanisms Featuring Causal Cycles

Published online by Cambridge University Press:  01 January 2022

Abstract

Mechanisms play an important role in many sciences when it comes to questions concerning explanation, prediction, and control. Answering such questions in a quantitative way requires a formal representation of mechanisms. Gebharter’s “A Formal Framework for Representing Mechanisms?” suggests to represent mechanisms by means of arrows in an acyclic causal net. In this article we show how this approach can be extended in such a way that it can also be fruitfully applied to mechanisms featuring causal feedback.

Type
Adequacy of Causal Graphs and Bayes Networks
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

This work was supported by Deutsche Forschungsgemeinschaft (DFG), research unit Causation|Laws|Dispositions|Explanation (FOR 1063). We thank Lorenzo Casini, David Danks, Christian J. Feldbacher, Clark Glymour, Marie I. Kaiser, Daniel Koch, Marcel Weber, and Naftali Weinberger for helpful remarks and discussions.

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