How to Infer from Inconsistent Beliefs without Revising?

Abstract

This paper investigates several methods for coping with inconsistency caused by multiple source information, by introducing suitable consequence relations capable of inferring non-trivial conclusions from an inconsistent stratified knowledge base. Some of these methods presuppose a revision step, namely a selection of one or several consistent subsets of formulas, and then classical inference is used for inferring from these subsets. Two alternative methods that do not require any revision step are studied: inference based on arguments, and a new approach called safely supported inference, where inconsistency is kept local. These two last methods look suitable when the inconsistency is due to the presence of several sources of information. The paper offers a comparative study of the various inference modes under inconsistency. 1 Introduction Inconsistency can be encountered in different reasoning tasks, in particular: - when reasoning with exception-tolerant generic knowledge, where ...