Abstract

Some of the information that we learn comes to us in a conditional form. This has proven to be a problem for philosophers, who try to explain how probabilistic beliefs change when one learns from conditional sentences. The problem is that a straight-forward solution is not possible: the partial belief in the antecedent and the partial belief in the consequent either increase, decrease, or remain the same. Two existing approaches to learning from indicative conditionals are considered: an explanatory one, and another that builds on relative information minimizing with regard to the causal structure. A novel method based on epistemic entrenchment is proposed to overcome the drawbacks of the competing approaches. The method solves all the standard examples and some other examples for which existing approaches have failed to provide adequate solutions.