Title :
Quasi-acyclic propositional Horn knowledge bases: optimal compression
Author :
Hammer, Peter L. ; Kogan, Alexander
Author_Institution :
RUTCOR, Rutgers Univ., New Brunswick, NJ, USA
fDate :
10/1/1995 12:00:00 AM
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;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on