Foundations of a Probabilistic Theory of Causal Strength
Year: 2018
Type: article
Abstract: This article develops axiomatic foundations for a probabilistic theory of causal strength as difference-making. I proceed in three steps: First, I motivate the choice of causal Bayes nets as an adequate framework for defining and comparing measures of causal strength. Second, I prove several representation theorems for probabilistic measures of causal strength—that is, I demonstrate how these measures can be derived from a set of plausible adequacy conditions. Third, I use these results to argue for a specific measure of causal strength: the difference that interventions on the cause make for the probability of the effect. I conclude by discussing my results and outlining future research avenues.
Source: The Philosophical Review
Author: Jan Sprenger
Institution: University of Turin
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2324700202