Approximate reasoning in strength logic

Author

Zhang, Hantao

Author_Institution

Dept. of Comput. Sci., Iowa Univ., Iowa City, IA, USA

fYear

1990

fDate

23-25 May 1990

Firstpage

262

Lastpage

269

Abstract

The author defines a modal logic SL (strength logic) to reason about beliefs in an AI system. SL is a refinement of J. Halpern and M. Rabin´s likelihood logic (LL) (1987). As in LL, the powers of a modal operator S are used in SL to denote various degrees of certainty of beliefs. However, the axiomatization of SL is different from that of LL. Formulas in SL admit normal forms, and decision procedures of SL can be effectively constructed. The author defines a model of SL as an extension of Herbrand models for the propositional logic. This interpretation of SL is sharply different from the conventional semantics of modal logics. The thrust behind this research is to provide a natural and rigorous logic for designing, implementing, and verifying AI systems capable of approximate reasoning

Keywords

formal logic; fuzzy logic; probability; AI system; Herbrand models; SL; approximate reasoning; beliefs; certainty factor; decision procedures; likelihood logic; modal logic; normal forms; propositional logic; strength logic; Artificial intelligence; Calculus; Cities and towns; Computer science; Expert systems; Fuzzy logic; Knowledge based systems; Logic design; Possibility theory; Power system modeling;

fLanguage

English

Publisher

ieee

Conference_Titel

Multiple-Valued Logic, 1990., Proceedings of the Twentieth International Symposium on

Conference_Location

Charlotte, NC

Print_ISBN

0-8186-2046-3

Type

conf

DOI

10.1109/ISMVL.1990.122631

Filename

122631