Measuring coherence with Bayesian networks

Artificial Intelligence and Law 31 (2):369-395 (2023)
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Abstract

When we talk about the coherence of a story, we seem to think of how well its individual pieces fit together—how to explicate this notion formally, though? We develop a Bayesian network based coherence measure with implementation in _R_, which performs better than its purely probabilistic predecessors. The novelty is that by paying attention to the network structure, we avoid simply taking mean confirmation scores between all possible pairs of subsets of a narration. Moreover, we assign special importance to the weakest links in a narration, to improve on the other measures’ results for logically inconsistent scenarios. We illustrate and investigate the performance of the measures in relation to a few philosophically motivated examples, and (more extensively) using the real-life example of the Sally Clark case.

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Author Profiles

Alicja Kowalewska
Carnegie Mellon University
Rafal Urbaniak
University of Gdansk

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Bayesian Epistemology.Luc Bovens & Stephan Hartmann - 2003 - Oxford: Oxford University Press. Edited by Stephan Hartmann.
Explanatory coherence (plus commentary).Paul Thagard - 1989 - Behavioral and Brain Sciences 12 (3):435-467.
Is coherence truth conducive?T. Shogenji - 1999 - Analysis 59 (4):338-345.
A probabilistic theory of coherence.B. Fitelson - 2003 - Analysis 63 (3):194-199.
Measuring coherence.Igor Douven & Wouter Meijs - 2007 - Synthese 156 (3):405 - 425.

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