Date of Original Version
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Abstract or Description
A successful theory of causal reasoning should be able to account for inferences about counterfactual scenarios. Pearl (2000) has developed a formal account of causal reasoning that has been highly influential but that suffers from at least two limitations as an account of counterfactual reasoning: it does not distinguish between counterfactual observations and counterfactual interventions, and it does not accommodate back- tracking counterfactuals. We present an extension of Pearl’s account that overcomes both limitations. Our model provides a unified treatment of counterfactual interventions and back- tracking counterfactuals, and we show that it accounts for data collected by Sloman and Lagnado (2005) and Rips (2010).
Proceedings of the 34th Annual Conference of the Cognitive Science Society.