Access Restriction

Author Pratt-Hartmann, Ian
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Abstract This paper employs epistemic logic to investigate the philosophical foundations of Bayesian updating in belief revision. By Bayesian updating, we understand the tenet that an agent’s degrees of belief—assumed to be encoded as a probability distribution—should be revised by conditionalization on the agent’s total knowledge up to that time. A familiar argument, based on the construction of a diachronic Dutch book, purports to show that Bayesian updating is the only rational belief-revision policy. We investigate the conditions under which of the premises of this argument might be satisfied. Specifically, we consider the case of an artificial agent whose language (of thought) features a modal operator TK, where TKψ has the interpretation “My total knowledge is ψ”. We show that every proposition of the form TKψ is epistemically categorical: it determines, for every proposition ϕ in the agent’s language, whether the agent knows that ϕ. We argue that, for certain artificial agents employing such
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article