If one models an agent's degrees of belief by a set of probabilities, how should that agent's choices be constrained?
In other words, what choice function should the agent use?
This paper summarises some suggestions, and outlines a collection of …

Imprecise probabilism, which holds that rational belief/credence is permissibly represented by a set of probability functions, apparently suffers from a problem known as *dilation*. We explore whether this problem can be avoided or mitigated by one …

There has been much recent interest in *imprecise probabilities*, models of belief that allow unsharp or fuzzy credence. There have also been some influential criticisms of this position. Here we argue, chiefly against Elga (2010), that subjective …

Here’s something I’ve been thinking about. The basic idea is to wonder what consequences follow from relaxing the standard assumption that Bayesian agents are logically omniscient.
Bayesian epistemology and decision theory typically assume that the ideal agents are logically omniscient. Borrowing a practice from I.J. Good, I refer to my putative ideal agent as “you”. That is, they assume that if $\phi$ and $\psi$ are logically equivalent, then you should believe them to the same degree.

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