Hans Tompits

Combining answer set programming with description logics for the Semantic Web

Towards the integration of rules and ontologies in the Semantic Web, we propose a combination of logic programming under the answer set semantics with the description logics SHIF(D) and SHOIN(D), which underly the Web ontology languages OWL Lite and OWL DL, respectively. This combination allows for building rules on top of ontologies but also, to a limited extent, building ontologies on top of rules. We introduce description logic programs (dl-programs), which consist of a description logic knowledge base L and a finite set of description logic rules (dl-rules) P. Such rules are similar to usual rules in logic programs with negation as failure, but may also contain queries to L, possibly default negated, in their bodies. We define Herbrand models for dl-programs, and show that satisfiable positive dl-programs have a unique least Her-brand model. More generally, consistent stratified dl-programs can be associated with a unique minimal Her-brand model that is characterized through iterative least Herbrand models. We then generalize the (unique) minimal Herbrand model semantics for positive and stratified dl-programs to a strong answer set semantics for all dl-programs, which is based on a reduction to the least model semantics of positive dl-programs. We also define a weak answer set semantics based on a reduction to the answer sets of ordinary logic programs. Strong answer sets are weak answer sets, and both properly generalize answer sets of ordinary normal logic programs. We then give fixpoint characterizations for the (unique) minimal Herbrand model semantics of positive and stratified dl-programs, and show how to compute these models by finite fixpoint iterations. Furthermore, we give a precise picture of the complexity of deciding strong and weak answer set existence for a dl-program.

Well-Founded Semantics for Description Logic Programs in the Semantic Web

In previous work, towards the integration of rules and ontologies in the Semantic Web, we have proposed a combination of logic programming under the answer set semantics with the description logics \({\cal SHIF}({\mathbf{D}})\) and \({\cal SHOIN}({\mathbf{D}})\), which underly the Web ontology languages OWL Lite and OWL DL, respectively. More precisely, we have introduced description logic programs (or dl-programs), which consist of a description logic knowledge base L and a finite set of description logic rules P, and we have defined their answer set semantics. In this paper, we continue this line of research. Here, as a central contribution, we present the well-founded semantics for dl-programs, and we analyze its semantic properties. In particular, we show that it generalizes the well-founded semantics for ordinary normal programs. Furthermore, we show that in the general case, the well-founded semantics of dl-programs is a partial model that approximates the answer set semantics, whereas in the positive and the stratified case, it is a total model that coincides with the answer set semantics. Finally, we also provide complexity results for dl-programs under the well-founded semantics.

Effective integration of declarative rules with external evaluations for semantic-web reasoning

Towards providing a suitable tool for building the Rule Layer of the Semantic Web, hex-programs have been introduced as a special kind of logic programs featuring capabilities for higher-order reasoning, interfacing with external sources of computation, and default negation. Their semantics is based on the notion of answer sets, providing a transparent interoperability with the Ontology Layer of the Semantic Web and full declarativity. In this paper, we identify classes of hex-programs feasible for implementation yet keeping the desirable advantages of the full language. A general method for combining and evaluating sub-programs belonging to arbitrary classes is introduced, thus enlarging the variety of programs whose execution is practicable. Implementation activity on the current prototype is also reported.

On properties of update sequences based on causal rejection

In this paper, we consider an approach to update nonmonotonic knowledge bases represented as extended logic programs under the answer set semantics. In this approach, new information is incorporated into the current knowledge base subject to a causal rejection principle, which enforces that, in case of conflicts between rules, more recent rules are preferred and older rules are overridden. Such a rejection principle is also exploited in other approaches to update logic programs, notably in the method of dynamic logic programming, due to Alferes et al.One of the central issues of this paper is a thorough analysis of various properties of the current approach, in order to get a better understanding of the inherent causal rejection principle. For this purpose, we review postulates and principles for update and revision operators which have been proposed in the area of theory change and nonmonotonic reasoning. Moreover, some new properties for approaches to updating logic programs are considered as well. Like related update approaches, the current semantics does not incorporate a notion of minimality of change, so we consider refinements of the semantics in this direction. We also investigate the relationship of our approach to others in more detail. In particular, we show that the current approach is semantically equivalent to inheritance programs, which have been independently defined by Buccafurri et al., and that it coincides with certain classes of dynamic logic programs. In view of this analysis, most of our results about properties of the causal rejection principle apply to each of these approaches as well. Finally, we also deal with computational issues. Besides a discussion on the computational complexity of our approach, we outline how the update semantics and its refinements can be directly implemented on top of existing logic programming systems. In the present case, we implemented the update approach using the logic programming system DLV.

A Classification and Survey of Preference Handling Approaches in Nonmonotonic Reasoning

In recent years, there has been a large amount of disparate work concerning the representation and reasoning with qualitative preferential information by means of approaches to nonmonotonic reasoning. Given the variety of underlying systems, assumptions, motivations, and intuitions, it is difficult to compare or relate one approach with another. Here, we present an overview and classification for approaches to dealing with preference. A set of criteria for classifying approaches is given, followed by a set of desiderata that an approach might be expected to satisfy. A comprehensive set of approaches is subsequently given and classified with respect to these sets of underlying principles.

A framework for compiling preferences in logic programs

We introduce a methodology and framework for expressing general preference information in logic programming under the answer set semantics. An ordered logic program is an extended logic program in which rules are named by unique terms, and in which preferences among rules are given by a set of atoms of form s p t where s and t are names. An ordered logic program is transformed into a second, regular, extended logic program wherein the preferences are respected, in that the answer sets obtained in the transformed program correspond with the preferred answer sets of the original program. Our approach allows the specification of dynamic orderings, in which preferences can appear arbitrarily within a program. Static orderings (in which preferences are external to a logic program) are a trivial restriction of the general dynamic case. First, we develop a specific approach to reasoning with preferences, wherein the preference ordering specifies the order in which rules are to be applied. We then demonstrate the wide range of applicability of our framework by showing how other approaches, among them that of Brewka and Eiter, can be captured within our framework. Since the result of each of these transformations is an extended logic program, we can make use of existing implementations, such as dlv and smodels. To this end, we have developed a publicly available compiler as a front-end for these programming systems.

Simplifying Logic Programs Under Uniform and Strong Equivalence

We consider the simplification of logic programs under the stable-model semantics, with respect to the notions of strong and uniform equivalence between logic programs, respectively. Both notions have recently been considered for nonmonotonic logic programs (the latter dates back to the 1980s, though) and provide semantic foundations for optimizing programs with input. Extending previous work, we investigate syntactic and semantic rules for program transformation, based on proper notions of consequence. We furthermore provide encodings of these notions in answer-set programming, and give characterizations of programs which are semantically equivalent to positive and Horn programs, respectively. Finally, we investigate the complexity of program simplification and determining semantical equivalence, showing that the problems range between coNP and \(\Pi_2^p\) complexity, and we present some tractable cases.

Encodings for Equilibrium Logic and Logic Programs with Nested Expressions

Equilibrium logic is an approach to nonmonotonic reasoning that generalises the stable model and answer set semantics for logic programs. We present a method to implement equilibrium logic and, as a special case, stable models for logic programs with nested expressions, based on polynomial reductions to quantified Boolean formulas (QBFs). Since there now exist efficient QBF-solvers, this reduction technique yields a practically relevant approach to rapid prototyping. The reductions for logic programs with nested expressions generalise previous results presented for other types of logic programs. We use these reductions to derive complexity results for the systems in question. In particular, we showthat deciding whether a program with nested expressions has a stable model is +2p -complete.

Modularity aspects of disjunctive stable models

Practically all programming languages allow the programmer to split a program into several modules which brings along several advantages in software development. In this paper, we are interested in the area of answer-set programming where fully declarative and nonmonotonic languages are applied. In this context, obtaining a modular structure for programs is by no means straightforward since the output of an entire program cannot in general be composed from the output of its components. To better understand the effects of disjunctive information on modularity we restrict the scope of analysis to the case of disjunctive logic programs (DLPs) subject to stable-model semantics. We define the notion of a DLP-function, where a well-defined input/output interface is provided, and establish a novel module theorem which indicates the compositionality of stable-model semantics for DLP-functions. The module theorem extends the well-known splitting-set theorem and enables the decomposition of DLP-functions given their strongly connected components based on positive dependencies induced by rules. In this setting, it is also possible to split shared disjunctive rules among components using a generalized shifting technique. The concept of modular equivalence is introduced for the mutual comparison of DLP-functions using a generalization of a translation-based verification method.

Reasoning with Rules and Ontologies

For realizing the Semantic Web vision, extensive work is underway for getting the layers of its conceived architecture ready. Given that the Ontology Layer has reached a certain level of maturity with W3C recommendations such as RDF and the OWL Web Ontology Language, current interest focuses on the Rules Layer and its integration with the Ontology Layer. Several proposals have been made for solving this problem, which does not have a straightforward solution due to various obstacles. One of them is the fact that evaluation principles like the closed-world assumption, which is common in rule languages, are usually not adopted in ontologies. Furthermore, naively adding rules to ontologies raises undecidability issues. In this paper, after giving a brief overview about the current state of the Semantic-Web stack and its components, we will discuss nonmonotonic logic programs under the answer-set semantics as a possible formalism of choice for realizing the Rules Layer. We will briefly discuss open issues in combining rules and ontologies, and survey some existing proposals to facilitate reasoning with rules and ontologies. We will then focus on description-logic programs (or dl-programs, for short), which realize a transparent integration of rules and ontologies supported by existing reasoning engines, based on the answer-set semantics. We will further discuss a generalization of dl-programs, viz.hex-programs, which offer access to different ontologies as well as higher-order language constructs.