A Quantitative Model of Counterfactual Reasoning

Daniel Yarlett, Michael Ramscar

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