FS-rules provide a powerful monotonic extension for Horn clauses that supports monotonic aggregates in recursion by reasoning on the multiplicity of occurrences satisfying existential goals. The least fixpoint semantics, and its equivalent least model semantics, hold for logic programs with FS-rules; moreover, generalized notions of stratification and stable models are easily derived when negated goals are allowed. Finally, the generalization of techniques such as seminaive fixpoint and magic sets, make possible the efficient implementation of DatalogFS, i.e., Datalog with rules with Frequency Support (FS-rules) and stratified negation. A large number of applications that could not be supported efficiently, or could not be expressed at all in stratified Datalog can now be easily expressed and efficiently supported in DatalogFS and a powerful DatalogFS system is now being developed at UCLA. Copyright © 2013 [MIRJANA MAZURAN, EDOARDO SERRA and CARLO ZANIOLO].

A declarative extension of horn clauses, and its significance for datalog and its applications

MAZURAN, MIRJANA;
2013

Abstract

FS-rules provide a powerful monotonic extension for Horn clauses that supports monotonic aggregates in recursion by reasoning on the multiplicity of occurrences satisfying existential goals. The least fixpoint semantics, and its equivalent least model semantics, hold for logic programs with FS-rules; moreover, generalized notions of stratification and stable models are easily derived when negated goals are allowed. Finally, the generalization of techniques such as seminaive fixpoint and magic sets, make possible the efficient implementation of DatalogFS, i.e., Datalog with rules with Frequency Support (FS-rules) and stratified negation. A large number of applications that could not be supported efficiently, or could not be expressed at all in stratified Datalog can now be easily expressed and efficiently supported in DatalogFS and a powerful DatalogFS system is now being developed at UCLA. Copyright © 2013 [MIRJANA MAZURAN, EDOARDO SERRA and CARLO ZANIOLO].
datalog; horn clauses; monotonic aggregates; stable models; Artificial Intelligence; Software; Hardware and Architecture; Theoretical Computer Science; Computational Theory and Mathematics
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1030512
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