A Rational and Efficient Algorithm for View Revision in Databases

TL;DR

This paper introduces a generalized, rational, and efficient algorithm for belief revision in databases, accommodating immutable beliefs and non-deductively closed states, with connections to kernel change and abduction.

Contribution

It extends belief revision theory to practical database scenarios by allowing immutable beliefs and non-deductive closure, providing a generalized revision algorithm for Horn knowledge bases.

Findings

The algorithm is rational and satisfies key belief dynamics postulates.

Connections established between Horn knowledge base revision, kernel change, and abduction.

The approach enhances belief revision efficiency and applicability in databases.

Abstract

The dynamics of belief and knowledge is one of the major components of any autonomous system that should be able to incorporate new pieces of information. In this paper, we argue that to apply rationality result of belief dynamics theory to various practical problems, it should be generalized in two respects: first of all, it should allow a certain part of belief to be declared as immutable; and second, the belief state need not be deductively closed. Such a generalization of belief dynamics, referred to as base dynamics, is presented, along with the concept of a generalized revision algorithm for Horn knowledge bases. We show that Horn knowledge base dynamics has interesting connection with kernel change and abduction. Finally, we also show that both variants are rational in the sense that they satisfy certain rationality postulates stemming from philosophical works on belief dynamics.