Proceedings of the Annual Meeting of the Cognitive Science Society

Conjunction fallacies (CF) have not only been a major obstacle in justifying the rationality of a Bayesian theory of belief update; they have also inspired a variety of theories on probability judgment and logical predication. Here we provide an overview of Bayesian logic (BL) as rational formulation of a pattern-based class of conjunction fallacies. BL is described here as a generalization of Bayesian Occam’s razor. BL captures the idea that probabilities are sometimes used not extensionally but intensionally, determining the probabilistic adequacy of ideal logical patterns. It is emphasized that BL is a class of models that depend on representations and the mea- nings of logical connectives. We discuss open questions and limits of BL. We also briefly discuss whether other theories of the CF may be good supplementary theories of CFs (and predication) as well, if linked to functional explanations.