Quantity implicatures, exhaustive interpretation, and rational conversation

Probabilistic pragmatics aspires to explain certain regularities of language use and interpretation as behavior of speakers and listeners who want to satisfy their conversational interests in a context that may contain a substantial amount of uncertainty. This approach differs substantially from more familiar approaches in theoretical pragmatics. To set it apart, we here work out some of its key distinguishing features and show, by way of some simple examples, how probabilistic pragmatics instantiates these.

In natural language conversations, speakers often communicate ‘if and only if’ when they say ‘if’. The reasons why in some circumstances, yet not all, conditionals receive a biconditional interpretation remain under investigation. Von Fintel (2001) proposed an account where the interpretation of a conditional (“if p, then q”) is predicted to depend on the focus of the conversation which may either lie on the conditions that make the consequent, q, true or on the consequences following when the antecedent, p, is true. To test this account, we present two novel behavioral experiments with non-text based stimuli that take advantage of participants’ intuitive understanding of physics. We find some supporting evidence for the tested account that is not conclusive but suggests that other aspects, like the nature of potential alternative causes for the consequent to become true (e.g., with or w/o the influence of an external variable), also play a role for the interpretation of the conditional.

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 indicative 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. EARLY ACCESS