Comparative Study of View Update Algorithms in Rational Choice Theory

TL;DR

This paper compares various view update algorithms within the rational choice framework, highlighting their theoretical connections and efficiency in belief and knowledge base dynamics.

Contribution

It provides a comprehensive comparison of view update algorithms in rational choice theory, integrating techniques like hitting set, abduction, and hyper tableaux calculus.

Findings

Different algorithms have unique strengths in belief update scenarios

The rational approach offers a unified perspective on view updates

Efficiency varies depending on the underlying computational techniques

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. We show that knowledge base dynamics has interesting connection with kernel change via hitting set and abduction. The approach extends and integrates standard techniques for efficient query answering and integrity checking. The generation of hitting set is carried out through a hyper tableaux calculus and magic set that is focused on the goal of minimality. Many different view update algorithms have been proposed in the literature to address this problem. The present paper provides a comparative study of view update algorithms in rational approach.