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Adams’s Thesis, the claim that the probabilities of indicative conditionals equal the conditional probabilities of their consequents given their antecedents, has proven impossible to accommodate within orthodox possibleworld semantics. This essay proposes a modification to the orthodoxy that removes this impossibility. The starting point is a proposal by Jeffrey and Stalnaker that conditionals take semantic values in the unit interval, interpreting these (à la McGee) as their expected truthvalues at a world. Their theories imply a false principle, namely, that the (...) 

This discussion note examines a recent argument for the principle that any counterfactual with true components is itself true. That argument rests upon two widely accepted principles of counterfactual logic to which the paper presents counterexamples. The conclusion speculates briefly upon the wider lessons that philosophers should draw from these examples for the semantics of counterfactuals. 



How should a group with different opinions (but the same values) make decisions? In a Bayesian setting, the natural question is how to aggregate credences: how to use a single credence function to naturally represent a collection of different credence functions. An extension of the standard Dutchbook arguments that apply to individual decisionmakers recommends that group credences should be updated by conditionalization. This imposes a constraint on what aggregation rules can be like. Taking conditionalization as a basic constraint, we gather (...) 



The article offers a rigorous truth condition for subjunctively conditional statements. The theory is framed in the system of transparent intensional logic and takes connections (especially the causeEffect relation) as basic. Counterexamples are given to rival theories based on the notion of world similarity. 







One very popular kind of semantics for subjunctive conditionals is aclosestworlds account along the lines of theories given by David Lewisand Robert Stalnaker. If we could give the same sort of semantics forindicative conditionals, we would have a more unified account of themeaning of ``if ... then ...'' statements, one with manyadvantages for explaining the behaviour of conditional sentences. Such atreatment of indicative conditionals, however, has faced a battery ofobjections. This paper outlines a closestworlds account of indicativeconditionals that does better (...) 









Conditionals give rise to standoffs that have become well known from Gibbard’s initial Sly Pete example. The standoffs can be seen as evidence for the contextsensitivity of conditionals and arguably do not involve disagreement. I claim that the latter feature lends credibility to an indexical treatment of indicatives. 

I present a puzzle concerning counterfactual reasoning and argue that it should be solved by giving up the principle of substitution for logical equivalents. 

The fact that the standard probabilistic calculus does not define probabilities for sentences with embedded conditionals is a fundamental problem for the probabilistic theory of conditionals. Several authors have explored ways to assign probabilities to such sentences, but those proposals have come under criticism for making counterintuitive predictions. This paper examines the source of the problematic predictions and proposes an amendment which corrects them in a principled way. The account brings intuitions about counterfactual conditionals to bear on the interpretation of (...) 



The aim of the paper is to draw a connection between a semantical theory of conditional statements and the theory of conditional probability. First, the probability calculus is interpreted as a semantics for truth functional logic. Absolute probabilities are treated as degrees of rational belief. Conditional probabilities are explicitly defined in terms of absolute probabilities in the familiar way. Second, the probability calculus is extended in order to provide an interpretation for counterfactual probabilitiesconditional probabilities where the condition has zero probability. (...) 



