Dynamics of Belief: Abduction, Horn Knowledge Base And Database Updates
Radhakrishnan Delhibabu

TL;DR
This paper presents a generalized framework for belief and knowledge base dynamics, incorporating immutable beliefs and non-deductively closed states, with applications to database updates using disjunctive logic programming techniques.
Contribution
It introduces base dynamics for belief revision allowing partial immutability and non-closure, and applies disjunctive logic programming for efficient database updates.
Findings
Generalized belief revision framework with immutable parts.
Disjunctive logic programming techniques improve database update efficiency.
Axiomatic characterization of belief and database update operations.
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 order to apply the rationality result of belief dynamics theory to various practical problems, it should be generalized in two respects: first 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 in this paper, along with the concept of a generalized revision algorithm for knowledge bases (Horn or Horn logic with stratified negation). We show that knowledge base dynamics has an interesting connection with kernel change via hitting set and abduction. In this paper, we show how techniques from disjunctive logic programming can be used for efficient (deductive) database…
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Taxonomy
TopicsLogic, Reasoning, and Knowledge · Advanced Algebra and Logic · Bayesian Modeling and Causal Inference
