Non-monotonic Negation in Probabilistic Deductive Databases
Abstract
In this paper we study the uses and the semantics of non-monotonic negation in probabilistic deductive data bases. Based on the stable semantics for classical logic programming, we introduce the notion of stable formula, functions. We show that stable formula, functions are minimal fixpoints of operators associated with probabilistic deductive databases with negation. Furthermore, since a. probabilistic deductive database may not necessarily have a stable formula function, we provide a stable class semantics for such databases. Finally, we demonstrate that the proposed semantics can handle default reasoning naturally in the context of probabilistic deduction.
Cite
@article{arxiv.1303.5735,
title = {Non-monotonic Negation in Probabilistic Deductive Databases},
author = {Raymond T. Ng and V. S. Subrahmanian},
journal= {arXiv preprint arXiv:1303.5735},
year = {2013}
}
Comments
Appears in Proceedings of the Seventh Conference on Uncertainty in Artificial Intelligence (UAI1991)