# Decision theory

## A Counterexample to Three Imprecise Decision Theories

There is currently much discussion about how decision making should proceed when an agent's degrees of belief are imprecise; represented by a set of probability functions. I show that decision rules recently discussed by Sarah Moss, Susanna Rinard …

## How to choose among choice functions

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 …

## Should subjective probabilities be sharp?

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 …

## Sure Loss and Logical Ignorance

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.