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 …

This project explores Imprecise probabilities as a model for rational belief.

It has been argued that imprecise probabilities are a natural and intuitive way of overcoming some of the issues with orthodox precise probabilities. Models of this type have a long pedigree, and interest in such models has been growing in recent …

This paper considers a puzzling conflict between
two positions that are each
compelling: (A) it is irrational for an agent to pay to avoid 'free' evidence
before making a decision, and (B) rational agents may have *imprecise*
beliefs and/or desires. …

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 …

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