Quasi-acyclic propositional Horn knowledge bases: optimal compression

Author

Hammer, Peter L. ; Kogan, Alexander

Author_Institution

RUTCOR, Rutgers Univ., New Brunswick, NJ, USA

Volume

7

Issue

5

fYear

1995

fDate

10/1/1995 12:00:00 AM

Firstpage

751

Lastpage

762

Abstract

Horn knowledge bases are widely used in many applications. The paper is concerned with the optimal compression of propositional Horn production rule bases-one of the most important knowledge bases used in practice. The problem of knowledge compression is interpreted as a problem of Boolean function minimization. It was proved by P.L. Hammer and A. Kogan (1993) that the minimization of Horn functions, i.e., Boolean functions associated with Horn knowledge bases, is NP complete. The paper deals with the minimization of quasi acyclic Horn functions, the class of which properly includes the two practically significant classes of quadratic and of acyclic functions. A procedure is developed for recognizing in quadratic time the quasi acyclicity of a function given by a Horn CNF, and a graph based algorithm is proposed for the quadratic time minimization of quasi acyclic Horn functions

Keywords

Boolean functions; Horn clauses; computational complexity; knowledge based systems; minimisation; Boolean function minimization; Horn CNF; Horn function minimisation; Horn knowledge bases; acyclic functions; graph based algorithm; knowledge compression; optimal compression; propositional Horn production rule bases; quadratic time minimization; quasi acyclic Horn functions; quasi acyclic propositional Horn knowledge bases; quasi acyclicity; Application software; Boolean functions; Computational complexity; Computer Society; Delay; Expert systems; Helium; Management information systems; Minimization methods; Production;

fLanguage

English

Journal_Title

Knowledge and Data Engineering, IEEE Transactions on

Publisher

ieee

ISSN

1041-4347

Type

jour

DOI

10.1109/69.469822

Filename

469822