The power of intervention

Minds and Machines 16 (3):289-302 (2006)
We further develop the mathematical theory of causal interventions, extending earlier results of Korb, Twardy, Handfield, & Oppy, (2005) and Spirtes, Glymour, Scheines (2000). Some of the skepticism surrounding causal discovery has concerned the fact that using only observational data can radically underdetermine the best explanatory causal model, with the true causal model appearing inferior to a simpler, faithful model (cf. Cartwright, (2001). Our results show that experimental data, together with some plausible assumptions, can reduce the space of viable explanatory causal models to one.
Keywords Causal models  Causal discovery  Faithfulness  Simplicity  Intervention  Bayesian networks  Underdetermination
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DOI 10.1007/s11023-006-9040-4
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References found in this work BETA
Peter Spirtes, Clark Glymour & Richard Scheines (1996). Causation, Prediction, and Search. British Journal for the Philosophy of Science 47 (1):113-123.

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Citations of this work BETA
Michael Baumgartner & Isabelle Drouet (2013). Identifying Intervention Variables. European Journal for Philosophy of Science 3 (2):183-205.

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