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Abstract:
In this paper we explore two quantitative approaches to the
modelling of counterfactual reasoning -- a linear and a noisy-OR
model -- based on information contained in conceptual dependency
networks. Empirical data is acquired in a study and the fit of
the models compared to it. We conclude by considering the
appropriateness of non-parametric approaches to counterfactual
reasoning, and examining the prospects for other parametric
approaches in the future.
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