Comparative Study of View Update Algorithms in Rational Choice Theory
This is an incremental study for researchers in autonomous systems and knowledge representation, focusing on comparing existing algorithms rather than introducing new ones.
The paper compares different view update algorithms in rational choice theory, showing that knowledge base dynamics connects to kernel change via hitting set and abduction while extending standard techniques for efficient query answering and integrity checking.
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.