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The expressiveness of locally stratified programs
Authors:Howard A. Blair  V. Wiktor Marek  John S. Schlipf
Affiliation:(1) School of Computer and Information Science, Syracuse University, 13244-4100 Syracuse, NY, USA;(2) Department of Computer Science, University of Kentucky, 40506 Lexington, KY, USA;(3) Department of Computer Science, University of Cincinnati, 45221-0008 Cincinnati, OH, USA
Abstract:This paper completes an investigation of the logical expressibility of finite, locally stratified, general logic programs. We show that every hyperarithmetic set can be defined by a suitably chosen locally stratified logic program (as a set of values of a predicate over its perfect model). This is an optimal result, since the perfect model of a locally stratified program is itself an implicitly definable hyperarithmetic set (under a recursive coding of the Herbrand base); hence, to obtain all hyperarithmetic sets requires something new, in this case selecting one predicate from the model. We find that the expressive power of programs does not increase when one considers the programs which have a unique stable model or a total well-founded model. This shows that all these classes of structures (perfect models of logically stratified logic programs, well-founded models which turn out to be total, and stable models of programs possessing a unique stable model) are all closely connected with Kleene's hyperarithmetical hierarchy. Thus, for general logic programming, negation with respect to two-valued logic is related to the hyperarithmetic hierarchy in the same way as Horn logic is to the class of recursively enumerable sets. In particular, a set is definable in the well-founded semantics by a programP whose well-founded partial model is total iff it is hyperarithmetic.Research partially supported by the U.S. Army Research Office through the Mathematical Sciences Institute of Cornell University.Research partially supported by NSF Grant IRI-9012902 and partially supported by the U.S. Army Research Office through the Mathematical Sciences Institute of Cornell University.Research partially supported by NSF Grant IRI-8905166 and partially supported by the U.S. Army Research Office through the Mathematical Sciences Institute of Cornell University.
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