A Logical Characterization of Evaluable Knowledge Bases

Alexander Sakharov

2022

Abstract

Evaluable knowledge bases are comprised of non-Horn rules with partial predicates and functions, some of them are defined as recursive functions. This paper investigates logical foundations of the derivation of literals from evaluable knowledge bases without reasoning by contradiction. The semantics of this inference is specified by constrained 3-valued models. The derivation of literals without reasoning by contradiction is characterized by means of sequent calculi with non-logical axioms expressing knowledge base rules and facts. The logical rules of these calculi include only the negation rules, and cut is the only essential structural rule.

Paper Citation

in Harvard Style

Sakharov A. (2022). A Logical Characterization of Evaluable Knowledge Bases. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-547-0, pages 681-688. DOI: 10.5220/0010886700003116

in Bibtex Style

@conference{icaart22,
author={Alexander Sakharov},
title={A Logical Characterization of Evaluable Knowledge Bases},
booktitle={Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2022},
pages={681-688},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010886700003116},
isbn={978-989-758-547-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
TI - A Logical Characterization of Evaluable Knowledge Bases
SN - 978-989-758-547-0
AU - Sakharov A.
PY - 2022
SP - 681
EP - 688
DO - 10.5220/0010886700003116