Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
Iterated Belief Revision, Reliability, and Inductive Kevin T. Kelly
 

Summary: Iterated Belief Revision, Reliability, and Inductive
Amnesia
Kevin T. Kelly
Department of Philosophy
Carnegie Mellon University
September 24, 2001
Abstract
Belief revision theory concerns methods for reformulating an agent's epistemic state when
the agent's beliefs are refuted by new information. The usual guiding principle in the
design of such methods is to preserve as much of the agent's epistemic state as possible
when the state is revised. Learning theoretic research focuses, instead, on a learning
method's reliability or ability to converge to true, informative beliefs over a wide range of
possible environments. This paper bridges the two perspectives by assessing the reliability
of several proposed belief revision operators. Stringent conceptions of "minimal change"
are shown to occasion a limitation called inductive amnesia: they can predict the future if
and only if they cannot remember the past. Avoidance of inductive amnesia can therefore
function as a plausible and hitherto unrecognized constraint on the design of belief revision
operators.
0.1 Introduction
According to the familiar, Bayesian account of probabilistic updating, full beliefs change

  

Source: Andrews, Peter B. - Department of Mathematical Sciences, Carnegie Mellon University

 

Collections: Mathematics