On Bayesian Measures of Evidential Support: Theoretical and Empirical Issues*

By Vincenzo Crupi, Katya Tentori, Michel Gonzalez. Philosophia Scientiæ, 2007

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A two-phase method for extracting explanatory arguments from Bayesian networks (2017, background): “See for a comparison the work of Crupi [36].”
State of the field: Measuring information and confirmation (2014, background): “Alternative theories of the expected utility of experiments or information search options raise issues that are similar to the plurality of confirmation measures (Brössel, 2013; Crupi et al., 2007; Festa, 1999; Fitelson, 1999).”
The Problem of Measure Sensitivity Redux (2013, background): “…satisfy both requirements. ðCarnap 1962Þ: dðH; EÞ5 PrðH jEÞ2 PrðHÞ; if PrðEÞ > 0. ðCarnap 1962Þ: rðH; EÞ5 PrðH \ EÞ2 PrðHÞ PrðEÞ: emarcation” has been adopted following Crupi et al. ð2007Þ. ðChristensen 1999; Joyce 1999Þ: SðH; EÞ5 PrðH jEÞ2 PrðH j:EÞ; if 1 > PrðEÞ > 0. ðCrupi et al. 2007Þ: ZðH;…”
A Second Look at the Logic of Explanatory Power (with Two Novel Representation Theorems) (2012, background): “…between ε*ðe; hÞ and yet another measure of confirmation, zðh; eÞ, which is based on the notion of the “relative distance” between the initial and final probability of a hypothesis (see Crupi, Tentori, and Gonzalez 2007; Crupi, Festa, and Buttasi 2010; Crupi and Tentori 2010, forthcoming): n. 8).”