While a large body of work has scrutinized the meaning of conditional sentences, considerably less attention has been paid to formal models of their pragmatic use and interpretation. Here, we take a probabilistic approach to pragmatic reasoning about conditionals which flexibly integrates gradient beliefs about richly structured world states. We model listeners' update of their prior beliefs about the causal structure of the world and the joint probabilities of the consequent and antecedent based on assumptions about the speaker's utterance production protocol. We show that, when supplied with natural contextual assumptions, our model uniformly explains a number of inferences attested in the literature, including epistemic inferences, Conditional Perfection and the dependency between antecedent and consequent of a conditional. We argue that this approach also helps explain three puzzles introduced by Douven (2012) about updating with conditionals: depending on the utterance context, the listener's belief in the antecedent may increase, decrease or remain unchanged.

翻译：虽然大量工作仔细审视了有条件判决的含义,但对其实际使用和解释的正式模式的注意却少得多。 在这里,我们对灵活整合结构丰富的世界国家的梯度信仰的有条件条件的务实推理采取了一种概率方法。 我们模拟了听众对世界因果结构以及由此而产生的共同可能性的先前信念的更新,这些信念是基于对演讲者言论制作协议的假设。 我们显示,在提供自然背景假设时,我们的模型一致解释了文献中证明的一些推论,包括缩略语推论、有条件完美以及前代人与后代有条件人之间的依赖性。 我们争辩说,这一方法也有助于解释杜文(2012年)关于有条件更新的三个难题:听者对前代人的信念可能增加、减少或保持不变。