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FDNC: Decidable nonmonotonic disjunctive logic programs with function symbols

FDNC: Decidable nonmonotonic disjunctive logic programs with function symbols We present the class FDNC of logic programs that allows for function symbols (F), disjunction (D), nonmonotonic negation under the answer set semantics (N), and constraints (C), while still retaining the decidability of the standard reasoning tasks. Thanks to these features, FDNC programs are a powerful formalism for rule-based modeling of applications with potentially infinite processes and objects, and which allows also for common-sense reasoning in this context. This is evidenced, for instance, by tasks in reasoning about actions and planning: brave and open queries over FDNC programs capture the well-known problems of plan existence and secure (conformant) plan existence, respectively, in transition-based actions domains. As for reasoning from FDNC programs, we show that consistency checking and brave/cautious reasoning tasks are ExpTime-complete in general, but have lower complexity under syntactic restrictions that give rise to a family of program classes. Furthermore, we also determine the complexity of open queries (i.e., with answer variables), for which deciding non-empty answers is shown to be ExpSpace -complete under cautious entailment. Furthermore, we present algorithms for all reasoning tasks that are worst-case optimal. The majority of them resorts to a finite representation of the stable models of an FDNC program that employs maximal founded sets of knots, which are labeled trees of depth at most 1 from which each stable model can be reconstructed. Due to this property, reasoning over FDNC programs can in many cases be reduced to reasoning from knots. Once the knot-representation for a program is derived (which can be done off-line), several reasoning tasks are not more expensive than in the function-free case, and some are even feasible in polynomial time. This knowledge compilation technique paves the way to potentially more efficient online reasoning methods not only for FDNC, but also for other formalisms. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Computational Logic (TOCL) Association for Computing Machinery

FDNC: Decidable nonmonotonic disjunctive logic programs with function symbols

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References (69)

Publisher
Association for Computing Machinery
Copyright
The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc.
Subject
Predicate logic
ISSN
1529-3785
DOI
10.1145/1656242.1656249
Publisher site
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Abstract

We present the class FDNC of logic programs that allows for function symbols (F), disjunction (D), nonmonotonic negation under the answer set semantics (N), and constraints (C), while still retaining the decidability of the standard reasoning tasks. Thanks to these features, FDNC programs are a powerful formalism for rule-based modeling of applications with potentially infinite processes and objects, and which allows also for common-sense reasoning in this context. This is evidenced, for instance, by tasks in reasoning about actions and planning: brave and open queries over FDNC programs capture the well-known problems of plan existence and secure (conformant) plan existence, respectively, in transition-based actions domains. As for reasoning from FDNC programs, we show that consistency checking and brave/cautious reasoning tasks are ExpTime-complete in general, but have lower complexity under syntactic restrictions that give rise to a family of program classes. Furthermore, we also determine the complexity of open queries (i.e., with answer variables), for which deciding non-empty answers is shown to be ExpSpace -complete under cautious entailment. Furthermore, we present algorithms for all reasoning tasks that are worst-case optimal. The majority of them resorts to a finite representation of the stable models of an FDNC program that employs maximal founded sets of knots, which are labeled trees of depth at most 1 from which each stable model can be reconstructed. Due to this property, reasoning over FDNC programs can in many cases be reduced to reasoning from knots. Once the knot-representation for a program is derived (which can be done off-line), several reasoning tasks are not more expensive than in the function-free case, and some are even feasible in polynomial time. This knowledge compilation technique paves the way to potentially more efficient online reasoning methods not only for FDNC, but also for other formalisms.

Journal

ACM Transactions on Computational Logic (TOCL) – Association for Computing Machinery

Published: Jan 1, 2010

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