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Conditionals are sentences of the form "If A, then B," and they play a central role in scientific, logical, and everyday reasoning. They have been in the philosophical limelight for centuries, and more recently, they have also been receiving attention from psychologists, linguists, and computer scientists. In spite of this, many key questions concerning conditionals remain unanswered. While most of the work on conditionals has addressed semantical questions -questions about the truth conditions of conditionals -this book focusses on the main epistemological questions that conditionals give rise to, such as: What are the probabilities of conditionals? When is a conditional acceptable or assertable? What do we learn when we receive new conditional information? In answering these questions, this book combines the formal tools of logic and probability theory with the experimental approach of cognitive psychology. It will be of interest to students and researchers in logic, epistemology, and the psychology of reasoning.igor douven is Directeur de Recherche at Sciences, normes, décision, Université Paris-Sorbonne. He has published widely on topics in formal epistemology, social epistemology, the philosophy of language, metaphysics, and cognitive science.

According to Adams's Thesis, the acceptability of an indicative conditional sentence goes by the conditional probability of its consequent given its antecedent. We test, for the first time, whether this thesis is descriptively correct and show that it is not; in particular, we show that it yields the wrong predictions for people's judgments of the acceptability of important subclasses of the class of inferential conditionals. Experimental results are presented that reveal an interaction effect between, on the one hand, the type of inferential connection between a conditional's antecedent and its consequent and, on the other, the judged acceptability of the conditional in relation to the conditional probability of its consequent given its antecedent. Specifically, these results suggest a family of theses, each pertaining to a different type of conditional, about how conditionals relate to the relevant conditional probabilities.

Intuition suggests that for a conditional to be evaluated as true, there must be some kind of connection between its component clauses. In this paper, we formulate and test a new psychological theory to account for this intuition. We combined previous semantic and psychological theorizing to propose that the key to the intuition is a relevance-driven, satisficing-bounded inferential connection between antecedent and consequent. To test our theory, we created a novel experimental paradigm in which participants were presented with a soritical series of objects, notably colored patches (Experiments 1 and 4) and spheres (Experiment 2), or both (Experiment 3), and were asked to evaluate related conditionals embodying non-causal inferential connections (such as "If patch number 5 is blue, then so is patch number 4"). All four experiments displayed a unique response pattern, in which (largely determinate) responses were sensitive to parameters determining inference strength, as well as to consequent position in the series, in a way analogous to belief bias. Experiment 3 showed that this guaranteed relevance can be suppressed, with participants reverting to the defective conditional. Experiment 4 showed that this pattern can be partly explained by a measure of inference strength. This pattern supports our theory's "principle of relevant inference" and "principle of bounded inference," highlighting the dual processing characteristics of the inferential connection.

Bayesians have traditionally taken a dim view of the Inference to the Best Explanation (IBE), arguing that, if IBE is at variance with Bayes' rule, then it runs afoul of the dynamic Dutch book argument. More recently, Bayes' rule has been claimed to be superior on grounds of conduciveness to our epistemic goal. The present paper aims to show that neither of these arguments succeeds in undermining IBE.