The dynamics of belief and knowledge is one of the major components of anyautonomous system that should be able to incorporate new pieces of information.In order to apply the rationality result of belief dynamics theory to variouspractical problems, it should be generalized in two respects: first it shouldallow a certain part of belief to be declared as immutable; and second, thebelief state need not be deductively closed. Such a generalization of beliefdynamics, referred to as base dynamics, is presented in this paper, along withthe concept of a generalized revision algorithm for knowledge bases (Horn orHorn logic with stratified negation). We show that knowledge base dynamics hasan interesting connection with kernel change via hitting set and abduction. Inthis paper, we show how techniques from disjunctive logic programming can beused for efficient (deductive) database updates. The key idea is to transformthe given database together with the update request into a disjunctive(datalog) logic program and apply disjunctive techniques (such as minimal modelreasoning) to solve the original update problem. The approach extends andintegrates standard techniques for efficient query answering and integritychecking. The generation of a hitting set is carried out through a hypertableaux calculus and magic set that is focused on the goal of minimality.
展开▼
