Selective Revision by Deductive Argumentation

PATRICK KRÜMPELMANN; MATTHIAS THIMM; MARCELO A. FALAPPA; ALEJANDRO J. GARCÍA; GABRIELE KERN-ISBERNER; GUILLERMO R. SIMARI

LECTURE NOTES IN COMPUTER SCIENCE

Springer

Lugar: Heidelberg; Año: 2012 vol. 7132 p. 147 - 162

0302-9743

The success postulate of classic belief revision theory demands that after revising some beliefs with by information the new information is believed. However, this form of prioritized belief revision is not apt under many circumstances. Research in non-prioritized belief revision investigates forms of belief revision where success is not a desirable property. Herein, selective revision uses a two step approach, first applying a transformation function to decide if and which part of the new information shall be accepted, and second, incorporating the result using a prioritized revision operator. In this paper, we implement a transformation function by employing deductive argumentation to assess the value of new information. Hereby we obtain a non-prioritizedrevision operator that only accepts new information if believing in the information is justfiable with respect to the beliefs. By making use of previous results on selective revision we prove that our revision operator satises several desirable properties. We illustrate the use of the revisionoperator by means of examples and compare it with related work.