Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
The Learning Power of Belief Revision Kevin T. Kelly
 

Summary: The Learning Power of Belief Revision
Kevin T. Kelly
Department of Philosophy
Carnegie Mellon University
kk3n@andrew.cmu.edu
Abstract
Belief revision theory aims to describe how one should change one's beliefs
when they are contradicted by newly input information. The guiding principle
of belief revision theory is to change one's prior beliefs as little as possible in
order to maintain consistency with the new information. Learning theory focuses,
instead, on learning power: the ability to arrive at true beliefs in a wide range
of possible environments. The goal of this paper is to bridge the two approaches
by providing a learning theoretic analysis of the learning power of belief revision
methods proposed by Spohn, Boutilier, Darwiche and Pearl, and others. The
results indicate that learning power depends sharply on details of the methods.
Hence, learning power can provide a well-motivated constraint on the design and
implementation of concrete belief revision methods.
1 Introduction
Intelligent systems act on the basis of fallible, general beliefs, such as "My car always stays
where I put it" or "rough objects of a given shape and size have more air resistance than

  

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

 

Collections: Mathematics