Complexity and undecidability results for logic programming

This paper surveys complexity, degree of uncomputability, and expressive power results for logic programming. Some major decision problem complexity results and other results for logic programming are also covered. It also proves several new results filling in previous gaps in the literature. The paper considers seven logic programming semantics: the van Emden-Kowalski semantics for definite (Horn) logic programs; the perfect model semantics for stratified and for locally stratified logic programs; and the two- and three-valued program completion semantics, the well-founded semantics, and the stable semantics, all for normal logic programs, under skeptical inference. The main results concern expressibility and query complexity/uncomputability in five contexts: for propositional logic programs, for first order logic programs with infinite Herbrand universes on their Herbrand universes (a closed domain assumption), for first order logic programs with infinite Herbrand universes on those universes extended with infinitely many new elements (an open domain assumption), and for logic programs without function or constant symbols evaluated over varying extensional databases (DATALOG-type results, data complexity results only) under both closed and open domain assumptions. Several of the open domain assumption results are new to this paper. Other results surveyed are (1) results about the family of all stable models of a program and (2) decision questions about when a logic program has nice properties with respect to a semantics (e.g., a unique stable model). One decision result, for well-founded semantics, is new to this paper.Work supported in part by NSF grant IRI-8905166.     

Logic programming with solution preferences

Preference logic programming (PLP) is an extension of logic programming for declaratively specifying problems requiring optimization or comparison and selection among alternative solutions to a query. PLP essentially separates the programming of a problem itself from the criteria specification of its solution selection. In this paper we present a declarative method for specifying preference logic programs. The method introduces a precise formalization for the syntax and semantics of PLP. The syntax of a preference logic program contains two disjoint sets of definite clauses, separating a core program specifying a general computational problem from its preference rules for optimization; the semantics of PLP is given based on the Herbrand model and fixed point theory, where how preferences affects the least Herbrand model of a logic program is interpreted as a sequence of meta-level mapping operations. In addition, we present an operational semantics based on a new resolution strategy and a memoized recursive algorithm for computing strictly stratified logic programs with well-formed preferences, and further show that the operational semantics of such a preference logic program is consistent to its declarative semantics.     

A metalogic programming approach: language,semantics and applications

Abstract

This paper presents a logic programming language of novel conception, called Reflective Prolog, which allows declarative metaknowledge representation and metareasoning. The language is defined by augmenting pure Prolog (Horn clauses) with capabilities of self-reference and logical reflection. Self-reference is designed as a quotation device (a carefully defined naming relation) which allows the construction of metalevel terms that refer to object-level terms and atoms. Logical reflection is designed as an unquotation mechanism (a distinguished truth predicate) which relates names to what is named, thus extending the meaning of domain predicates. The reflection mechanism is embodied in an extended resolution procedure which automatically switches the context between levels. This implicit reflection relieves the programmer from having to explicitly deal with control aspects of the inference process. The declarative semantics of a Reflective Prolog definite program P is provided in terms of the least reflective Herbrand model of P, characterized by means of a suitable mapping defined over the Herbrand interpretations of P. The extended resolution is proved sound and complete with respect to the least reflective Herbrand model. By illustrating Reflective Prolog solutions to an organic set of problems, and by discussing the main differences with respect to other approaches to logic metaprogramming, we show that the proposed language deploys, within its field of action, greater expressive and inferential power than those available till now. The interpreter of the language has been fully implemented. Because of its enhanced power, logic semantics and working interpreter, Reflective Prolog is offered as a contribution toward making the declarative approach of logic programming applicable to the development of increasingly sophisticated knowledge-based systems.     

Why untyped nonground metaprogramming is not (much of) a problem

We study a semantics for untyped, vanilla metaprograms, using the nonground representation for object level variables. We introduce the notion of language independence, which generalizes range restriction. We show that the vanilla metaprogram associated with a stratified normal object program is weakly stratified. For language independent, stratified normal object programs, we prove that there is a natural one-to-one correspondence between atoms p(t₁,…,t_r) in the perfect Herbrand model of the object program and solve(p(t₁,…,t_r)) atoms in the weakly perfect Herb and model of the associated vanilla metaprogram. Thus, for this class of programs, the weakly perfect Herbrand model provides a sensible semantics for the metaprogram. We show that this result generalizes to nonlanguage independent programs in the context of an extended Herbrand semantics, designed to closely mirror the operational behavior of logic programs. Moreover, we also consider a number of interesting extensions and/or variants of the basic vanilla metainterpreter. For instance, we demonstrate how our approach provides a sensible semantics for a limited form of amalgamation.     

Compositional model-theoretic semantics for logic programs

We present a compositional model-theoretic semantics for logic programs, where the composition of programs is modelled by the composition of the admissible Herbrand models of the programs. An Herbrand model is admissible if it is supported by the assumption of a set of hypotheses. On one hand, the hypotheses supporting a model correspond to an open interpretation of the program intended to capture possible compositions with other programs. On the other hand, admissible models provide a natural model-theory for a form of hypothetical reasoning, called abduction. The application of admissibel models to programs with negation is discussed. Antonio Brogi: Dipartimento di Informatica, Università di Pisa, Corso Italia 40, 56125 Pisa, ItalyResearch interests: Programming Language Design and Semantics, Logic Programming and Artificial Intelligence     

Bounded Nondeterminism of Logic Programs

We introduce the notion of bounded nondeterminism for logic programs and queries. A program and a query have bounded nondeterminism if there are finitely many refutations for them via any selection rule. We offer a declarative characterization of the class of programs and queries that have bounded nondeterminism by defining bounded programs and queries. The characterization is provided in terms of Herbrand interpretations and level mappings, in the style of existing characterizations of universal termination. A direct application of the theoretical framework is concerned with the automatic generation of a terminating control. We present a transformational approach that given a bounded program and a bounded query yields a terminating program and query with the same set of refutations. Concerning the issue of automating the approach, by means of an example we sketch how an automatic method for proving left termination can be adapted to the purpose of inferring boundedness. Such an adaption reveals that the method does not scale up to medium/large sized programs due to scarce modularity of the required proof obligations. We provide then a modular refinement of boundedness for the significant class of well-moded programs and queries.     

On computability by logic programs

The problem of computational completeness of Horn clause logic programs is revisited. The standard results on representability of all computable predicates by Horn clause logic programs are not related to the real universe on which logic programs operate. SLD-resolution, which is the main mechanism to execute logic programs, may give answer substitutions with variables. As the main result we prove that computability by Horn clause logic programs is equivalent to standard computability over the Herbrand universe with variables. The semantics we use isS-semantics introduced by Falaschi et al. [3]. As an application of the main result we prove the existence of a metainterpreter for a sublanguage of real Prolog, written in the language of Horn clauses with the S-semantics. We also show that the traditional semantics of Prolog do not reflect its computational behavior from the viewpoint of recursion theory.This article is a revised version of [13]. The work was essentially done during author's visit to ECRC.     

F-logic语言表达能力的研究

F-logic语言是一种基于框架逻辑的逻辑数据语言，它在表示面向对象的特征方面具有较强的能力，但是讨论其操作复杂对象能力的工作还不多见.本文比较了以COL，（complexobjectlanguage）为代表的逻辑数据语言与F-logic语言操作复杂对象的能力.通过两对保持语义的变换，能够将F-logic程序及其Herbrand解释与COL，程序及其Herbrand解释互相转变，且保持程序在相应解释下的真值性质.最后，讨论了否定的影响.本文的工作说明:在不考虑F-logic语言oid生成影响的情况下，F-logic语言与COL，LDL1和ELPS等逻辑数据语言在操作复杂对象方面具有相同的能力.     

On the Expressive Power of F-Logic Language

F-logic language is a logic database language based on frame logic.It is powerful in expressing object-oriented features.However,there was little work discussing its capability of manipulating complex objects.In this paper,the authors compare the capability of F-logic with that of logic database languages represented by COL.Through two pairs of semantic-preserving transformations,F-logic progams and their corresponding Herbrand interpretations,and vice versa.Also,the effects of negation are discussed.The results of this paper indicate that,without consideration of the effects of OID generating,F-logic language has the same power in manipulatin complex objects as COL,LDL1,and ELPS.     

Quantitative deduction and its fixpoint theory

Logic programming provides a model for rule-based reasoning in expert systems. The advantage of this formal model is that it makes available many results from the semantics and proof theory of first-ordet predicate logic. A disadvantage is that in expert systems one often wants to use, instead of the usual two truth values, an entire continuum of “uncertainties” in between. That is, instead of the usual “qualitative” deduction, a form of “quantitative” deduction is required. We present an approach to generalizing the Tarskian semantics of Horn clause rules to justify a form of quantitative deduction. Each clause receives a numerical attenuation factor. Herbrand interpretations, which are subsets of the Herbrand base, are generalized to subsets which are fuzzy in the sense of Zadeh. We show that as result the fixpoint method in the semantics of Horn clause rules can be developed in much the same way for the quantitative case. As for proof theory, the interesting phenomenon is that a proof should be viewed as a two-person game. The value of the game turns out to be the truth value of the atomic formula to be proved, evaluated in the minimal fixpoint of the rule set. The analog of the PROLOG interpreter for quantitative deduction becomes a search of the game tree ( = proof tree) using the alpha-beta heuristic well known in game theory.     

A confluent semantic basis for the analysis of concurrent constraint logic programs

The standard operational semantics of concurrent constraint logic languages is not confluent in the sense that different schedulings of processes may result in different program behaviors. While implementations are free to choose specific scheduling policies, analyses should be correct for all implementations. Moreover, in the presence of parallelism, it is usually not possible to determine how processes will actually be scheduled. Efficient program analysis is therefore difficult as all process schedulings must be considered. To overcome this problem, we introduce a confluent semantics which closely approximates the standard (nonconfluent) semantics. This semantics provides a basis for efficient and accurate program analysis for these languages. To illustrate the usefulness of this approach, we sketch analyses based on abstract interpretations of the confluent semantics which determine if a program is suspension- and local suspension-free.     

Herbrand基上的启发式语义映射

一、引言 在逻辑程序中允许负文字出现,极大地增强了逻辑程序的表达能力,但同时也其语义定义带来了困难。可以说,至今还没有一种好的方法来定义一般逻辑程序的语义。     

A semantical framework for supporting subjective and conditional probabilities in deductive databases

We present a theoretical basis for supporting subjective and conditional probabilities in deductive databases. We design a language that allows a user greater expressive power than classical logic programming. In particular, a user can express the fact thatA is possible (i.e.A has non-zero probability),B is possible, but (A B) as a whole is impossible. A user can also freely specify probability annotations that may contain variables. The focus of this paper is to study the semantics of programs written in such a language in relation to probability theory. Our model theory which is founded on the classical one captures the uncertainty described in a probabilistic program at the level of Herbrand interpretations. Furthermore, we develop a fixpoint theory and a proof procedure for such programs and present soundness and completeness results. Finally we characterize the relationships between probability theory and the fixpoint, model, and proof theory of our programs.     

Logic programming in tensor spaces

Annals of Mathematics and Artificial Intelligence - This paper introduces a novel approach to computing logic programming semantics. First, a propositional Herbrand base is represented in a vector...     

A type system for logic programs

A theory for a type system for logic programs is developed which addressesthe question of well-typing, type inference, and compile-time and run-time type checking. A type is a recursively enumerable set of ground atoms, which is tuple-distributive. The association of a type to a program is intended to mean that only ground atoms that are elements of the type may be derived from the program. A declarative definition of well-typed programs is formulated, based on an intuitive approach related to the fixpoint semantics of logic programs. Whether a program is well typed is undecidable in general. We define a restricted class of types, called regular types, for which type checking is decidable. Regular unary logic programs are proposed as a specification language for regular types. An algorithm for type-checking a logic program with respect to a regular type definition is described, and its complexity is analyzed. Finally, the practicality of the type system is discussed, and some examples are shown. The type system has been implemented in FCP for FCP and is incorporated in the Logix system.     

On the autoepistemic reconstruction of logic programming

Current semantics of logic programs normally ignore thesyntactical aspects of the programs. As a result, only the meanings ofsome well-behaved programs can be captured by these semantics. In this paper however, we propose a new semantics of logic programs that can reflectsome of the syntactical behaviours of the programs. The central notion of the semantics is the concept of aneutral clause p ← A which does not affect the behaviour of p in a program. The logic that underlies the semantics is based on anintensional extension of Levesque’s autoepistemicpredicate logic. It differs from existing autoepistemic logics in that it isquantificational andconstructive. We will also compare and contrast our semantics with some well-known semantics. In particular, we will show how to capture the undefined value of a logic program without resorting to a three-valued nonmonotonic formalism. This is achieved by translating an incoherent AE logic program to a program with multiple AE extensions whose intersection can then be used to characterize the undefined value of a logic program.     

The expressiveness of locally stratified programs

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.     

解释学习结果的优化排序

解释学习可以直接应用于知识库的推理加速．经解释学习学到的一组规则,其参加匹配的先后次序直接影响着学习的效用．本文提出并证明了在以规则的成功频率与本身匹配费用的比值为序自大至小排列时,可以使这些规则的整体匹配费用最小．文中给出学习结果的优化排序算法,对于训练例的任意给定次序,可求得最小费用排列．     

Contributions to the semantics of logic perpetual processes

Summary Logic perpetual processes (logic programs with infinite data structures) have been given several formal (operational and fixpoint) semantics. In this paper, we compare the various semantics and define a formal characterization of a least fixpoint semantics, which is based on a modified version of the logic programs and which is satisfactory for a large class of logical perpetual processes. Our results show that all the proposed fixpoint semantics are not equivalent to the operational semantics and suggest an improvement of the least fixpoint approach.