A Rational and Efficient Algorithm for View Revision in Databases
This work addresses the need for rational belief revision in autonomous systems, but it appears incremental as it builds on existing theory with specific generalizations.
The paper tackles the problem of applying belief dynamics theory to practical scenarios by generalizing it to allow immutable beliefs and non-deductively closed states, presenting a base dynamics approach and a revision algorithm for Horn knowledge bases, and showing that these variants satisfy rationality postulates.
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.