Communicating uncertain beliefs with conditionals: Probabilistic modeling and experimental data

Abstract

Conditionals like If A, then C can be used, among others, to convey important knowledge about rules, dependencies and causal relationships. Much work has been devoted to the interpretation of conditional sentences, but much less is known about when speakers choose to use a conditional over another type of utterance in communication. To fill this gap, we consider a recently proposed computational model from probabilistic pragmatics, adapted for modeling the use of conditionals in natural language, by comparing its predictions to experimental production data from a behavioral experiment. In a novel experimental approach, we manipulate relevant causal beliefs that might influence whether utterances with conditional structure are preferred over utterances without conditional structure. This is a step towards a systematic, quantitative investigation of the situations that do or do not elicit the natural use of conditionals. © Cognitive Science Society: Comparative Cognition: Animal Minds, CogSci 2021.All rights reserved.