Gelfond and Zhang recently proposed a new stable model semantics based on Vicious Circle Principle in order to improve the interpretation of logic programs with aggregates. The paper focuses on this proposal, and analyzes the complexity of both coherence testing and cautious reasoning under the new semantics. Some surprising results highlight similarities and differences versus mainstream stable model semantics for aggregates. Moreover, the paper reports on the design of compilation techniques for implementing the new semantics on top of existing ASP solvers, which eventually lead to realize a prototype system that allows for experimenting with Gelfond-Zhang's aggregates. To appear in Theory and Practice of Logic Programming (TPLP), Proceedings of ICLP 2015.
A detailed complexity analysis for F-stable models is reported in @cite_6 and summarized in Table . Complexity of reasoning under stable models by @cite_3 @cite_9 , instead, is analyzed in @cite_14 , where in particular @math -completeness of coherence testing is proved for disjunction-free programs with aggregates. Concerning G-stable models, the general case was studied in @cite_8 , and a more detailed analysis is provided by this paper. In particular, for disjunction-free programs, the main reasoning tasks are in the first level of the polynomial hierarchy in general when G-stable models are used. On the other hand, coherence testing jumps from @math to @math when F-stable models are replaced by G-stable models in programs with monotone aggregates only. Indeed, in constrast to previous semantics, monotone aggregates are enough to simulate integrity constraints and negation when G-stable models are used.
@cite_14 @cite_8 @cite_9 @cite_3 @cite_6
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Recently Ferraris, Lee and Lifschitz proposed a new definition of stable models that does not refer to grounding, which applies to the syntax of arbitrary first-order sentences. We show its relation to the idea of loop formulas with variables by Chen, Lin, Wang and Zhang, and generalize their loop formulas to disjunctive programs and to arbitrary first-order sentences. We also extend the syntax of logic programs to allow explicit quantifiers, and define its semantics as a subclass of the new language of stable models by Such programs inherit from the general language the ability to handle nonmonotonic reasoning under the stable model semantics even in the absence of the unique name and the domain closure assumptions, while yielding more succinct loop formulas than the general language due to the restricted syntax. We also show certain syntactic conditions under which query answering for an extended program can be reduced to entailment checking in first-order logic, providing a way to apply first-order theorem provers to reasoning about non-Herbrand stable models. Partial stable models for deductive databases, i.e., normal function-free logic programs (also called datalog programs), have two equivalent definitions: one based on 3-valued logics and another based on the notion of unfounded set. The notion of partial stable model has been extended to disjunctive deductive databases using 3-valued logics. In this paper, a characterization of partial stable models for disjunctive datalog programs is given using a suitable extension of the notion of unfounded set. Two interesting sub-classes of partial stable models, M-stable (Maximal-stable) (also called regular models, preferred extension,and maximal stable classes) and L-stable (Least undefined-stable) models, are then extended from normal to disjunctive datalog programs. On the one hand, L-stable models are shown to be the natural relaxation of the notion of total stable model; on the other hand the less strict M-stable models, endowed with a nice modularity property, may be appealing from the programming and computational point of view. M-stable and L-stable models are also compared with the regular models for disjunctive datalog programs recently proposed in the literature. Let P be an arbitrary theory and let X be any given logic. Let M be a set of atoms. We say that M is a X-stable model of P if M is a classical model of P and P∪¬M proves in logic X all atoms in M, this is denoted by P∪¬M ⊩xM. We prove that being an X-stable model is an invariant property for disjunctive programmes under a large class of logics. Two kinds of logics are mainly considered: paraconsistent logics and normal modal logics. For modal logics we use a translation proposed by Gelfond that replaces ¬a with ¬□a. As a consequence we prove that several semantics (recently introduced) for non-monotonic reasoning are equivalent for disjunctive programmes. In addition, we show that such semantics can be characterized by a fixed-point operator in terms of classical logic. We also present a simple translation of a disjunctive programme D into a normal programme N, such that the PStable model semantics of N corresponds to the stable semantics of D over the common language. We present the formal proof of this statement. We present an implementation of the general language of stable models proposed by Ferraris, Lee and Lifschitz. Under certain conditions, system f2lp turns a first-order theory under the stable model semantics into an answer set program, so that existing answer set solvers can be used for computing the general language. Quantifiers are first eliminated and then the resulting quantifier-free formulas are turned into rules. Based on the relationship between stable models and circumscription, f2lp can also serve as a reasoning engine for general circumscriptive theories. We illustrate how to use f2lp to compute the circumscriptive event calculus.