A causal Bayes net analysis of dispositions

Florian Fischer, Alexander Gebharter

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Abstract

In this paper we develop an analysis of dispositions by means of causal Bayes nets. In particular, we analyze dispositions as cause-effect structures that increase the probability of the manifestation when the stimulus is brought about by intervention in certain circumstances. We then highlight several advantages of our analysis and how it can handle problems arising for classical analyses of dispositions such as masks, mimickers, and finks.
Original languageEnglish
JournalSynthese
Early online date29-Aug-2019
DOIs
Publication statusE-pub ahead of print - 29-Aug-2019

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