Notes
Another somewhat unusual methodological feature of the book is the occasional use of computer modeling.
Here I will only review one of two responses discussed by S & H.
I should add that addressing this problem is not the main concern in Variation 12.
It is sometimes thought that imaging (Lewis 1976) is the counterfactual counterpart to conditionalization, but imaging is not going to do what we need it to here. Imaging deals with the case where we are updating p(H) on counterfactual evidence E. But the case we are interested in here is how to update p(H|M) (i.e. a counterfactual degree of belief in H given M) on actual evidence E.
References
Bernardo, J. M., & Smith, A. F. M. (2000). Bayesian theory. Wiley.
Fahrbach, L. (2011). How the growth of science ends theory change. Synthese, 180(2), 139–155.
Forster, M., & Sober, E. (1994). How to tell when simpler, more unified, or less Ad Hoc theories will provide more accurate predictions. British Journal for the Philosophy of Science, 45(1), 1–35.
Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian data analysis (3rd ed.). CRC Press.
Glymour, C. (1980). Theory and evidence. Princeton University Press.
Laudan, L. (1981). A confutation of convergent realism. Philosophy of Science, 48(1), 19–49.
Lewis, D. (1976). Probabilities of conditionals and conditional probabilities. Philosophical Review, 85(3), 297–315.
Mayo, D. (1996). Error and the growth of experimental knowledge. University of Chicago Press.
Williams, P. M. (1980). Bayesian Conditionalisation and the Principle of Minimum Information. British Journal for the Philosophy of Science, 31(2), 131–144.
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Vassend, O.B. Review of Bayesian Philosophy of Science. Erkenn 88, 2245–2249 (2023). https://doi.org/10.1007/s10670-021-00431-8
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DOI: https://doi.org/10.1007/s10670-021-00431-8