Query Evaluation in Deductive Databases

It is desirable to answer queries posed to deductive databases by computing fixpoints because such computations are directly amenable to set-oriented fact processing. However, the classical fixpoint procedures based on bottom-up processing — the naive and semi-naive methods — are rather primitive and often inefficient. In this article, we rely on bottom-up meta-interpretation for formalizing a new fixpoint procedure that performs a different kind of reasoning: We specify a top-down query answering method, which we call the Backward Fixpoint Procedure. Then, we reconsider query evaluation methods for recursive databases. First, we show that the methods based on rewriting on the one hand, and the methods based on resolution on the other hand, implement the Backward Fixpoint Procedure. Second, we interpret the rewritings of the Alexander and Magic Set methods as specializations of the Backward Fixpoint Procedure. Finally, we argue that such a rewriting is also needed in a database context for implementing efficiently the resolution-based methods. Thus, the methods based on rewriting and the methods based on resolution implement the same top-down evaluation of the original database rules by means of auxiliary rules processed bottom-up

Distributed Abductive Reasoning: Theory, Implementation and Application

Abductive reasoning is a powerful logic inference mechanism that allows assumptions to be made during answer computation for a query, and thus is suitable for reasoning over incomplete knowledge. Multi-agent hypothetical reasoning is the application of abduction in a distributed setting, where each computational agent has its local knowledge representing partial world and the union of all agents' knowledge is still incomplete. It is different from simple distributed query processing because the assumptions made by the agents must also be consistent with global constraints. Multi-agent hypothetical reasoning has many potential applications, such as collaborative planning and scheduling, distributed diagnosis and cognitive perception. Many of these applications require the representation of arithmetic constraints in their problem specifications as well as constraint satisfaction support during the computation. In addition, some applications may have confidentiality concerns as restrictions on the information that can be exchanged between the agents during their collaboration. Although a limited number of distributed abductive systems have been developed, none of them is generic enough to support the above requirements. In this thesis we develop, in the spirit of Logic Programming, a generic and extensible distributed abductive system that has the potential to target a wide range of distributed problem solving applications. The underlying distributed inference algorithm incorporates constraint satisfaction and allows non-ground conditional answers to be computed. Its soundness and completeness have been proved. The algorithm is customisable in that different inference and coordination strategies (such as goal selection and agent selection strategies) can be adopted while maintaining correctness. A customisation that supports confidentiality during problem solving has been developed, and is used in application domains such as distributed security policy analysis. Finally, for evaluation purposes, a flexible experimental environment has been built for automatically generating different classes of distributed abductive constraint logic programs. This environment has been used to conduct empirical investigation of the performance of the customised system

Issues in concurrent knowledge engineering : knowledge sharing and knowledge base evolution

The development of knowledge-based (KB) systems for solving real-world problems has become a very time-consuming and expensive task. Over the last years, more and more people started to investigate how to share and reuse knowledge once it has been formally represented. Moreover, as the world around is changing continuously, the KB system and its knowledge base have to change, too. Thus, recently the issue of knowledge base evolution came up that deals with the continuous improvement of a KB system during its entire life-time starting with the first formalizations and still continuing along its practical use. We discuss the current efforts in knowledge sharing and reuse and then study the knowledge evolution approach, that can be seen more technically as an interleaved combination of knowledge validation and exploration techniques

Every normal logic program has a 2-valued semantics: theory, extensions, applications, implementations

Trabalho apresentado no âmbito do Doutoramento em Informática, como requisito parcial para obtenção do grau de Doutor em InformáticaAfter a very brief introduction to the general subject of Knowledge Representation and Reasoning with Logic Programs we analyse the syntactic structure of a logic program and how it can influence the semantics. We outline the important properties of a 2-valued semantics for Normal Logic Programs, proceed to define the new Minimal Hypotheses semantics with those properties and explore how it can be used to benefit some knowledge representation and reasoning mechanisms. The main original contributions of this work, whose connections will be detailed in the sequel, are: • The Layering for generic graphs which we then apply to NLPs yielding the Rule Layering and Atom Layering — a generalization of the stratification notion; • The Full shifting transformation of Disjunctive Logic Programs into (highly nonstratified)NLPs; • The Layer Support — a generalization of the classical notion of support; • The Brave Relevance and Brave Cautious Monotony properties of a 2-valued semantics; • The notions of Relevant Partial Knowledge Answer to a Query and Locally Consistent Relevant Partial Knowledge Answer to a Query; • The Layer-Decomposable Semantics family — the family of semantics that reflect the above mentioned Layerings; • The Approved Models argumentation approach to semantics; • The Minimal Hypotheses 2-valued semantics for NLP — a member of the Layer-Decomposable Semantics family rooted on a minimization of positive hypotheses assumption approach; • The definition and implementation of the Answer Completion mechanism in XSB Prolog — an essential component to ensure XSB’s WAM full compliance with the Well-Founded Semantics; • The definition of the Inspection Points mechanism for Abductive Logic Programs;• An implementation of the Inspection Points workings within the Abdual system [21] We recommend reading the chapters in this thesis in the sequence they appear. However, if the reader is not interested in all the subjects, or is more keen on some topics rather than others, we provide alternative reading paths as shown below. 1-2-3-4-5-6-7-8-9-12 Definition of the Layer-Decomposable Semantics family and the Minimal Hypotheses semantics (1 and 2 are optional) 3-6-7-8-10-11-12 All main contributions – assumes the reader is familiarized with logic programming topics 3-4-5-10-11-12 Focus on abductive reasoning and applications.FCT-MCTES (Fundação para a Ciência e Tecnologia do Ministério da Ciência,Tecnologia e Ensino Superior)- (no. SFRH/BD/28761/2006

The CIFF Proof Procedure for Abductive Logic Programming with Constraints: Definition, Implementation and a Web Application

Abduction has found broad application as a powerful tool for hypothetical reasoning with incomplete knowledge, which can be handled by labeling some pieces of information as abducibles, i.e. as possible hypotheses that can be assumed to hold, provided that they are consistent with the given knowledge base. Attempts to make the abductive reasoning an effective computational tool gave rise to Abductive Logic Programming (ALP) which combines abduction with standard logic programming. A number of so-called proof procedures for ALP have been proposed in the literature, e.g. the IFF procedure, the Kakas and Mancarella procedure and the SLDNFA procedure, which rely upon extensions of different semantics for logic programming. ALP has also been integrated with Constraint Logic Programming (CLP), in order to combine abductive reasoning with an arithmetic tool for constraint solving. In recent years, many proof procedures for abductive logic programming with constraints have been proposed, including ACLP and the A-System which have been applied to many fields, e.g. multi-agent systems, scheduling, integration of information. This dissertation describes the development of a new abductive proof procedure with constraints, namely the CIFF proof procedure. The description is both at the theoretical level, giving a formal definition and a soundness result with respect to the three-valued completion semantics, and at the implementative level with the implemented CIFF System 4.0 as a Prolog meta-interpreter. The main contributions of the CIFF proof procedure are the advances in the expressiveness of the framework with respect to other frameworks for abductive logic programming with constraints, and the overall computational performances of the implemented system. The second part of the dissertation presents a novel application of the CIFF proof procedure as the computational engine of a tool, the CIFFWEB system, for checking and (possibly) repairing faulty web sites. Indeed, the exponential growth of the WWW raises the question of maintaining and automatically repairing web sites, in particular when the designers of these sites require them to exhibit certain properties at both structural and data level. The capability of maintaining and repairing web sites is also important to ensure the success of the Semantic Web vision. As the Semantic Web relies upon the definition and the maintenance of consistent data schemas (XML/XMLSchema, RDF/RDFSchema, OWL and so on), tools for reasoning over such schemas (and possibly extending the reasoning to multiple web pages) show great promise. The CIFFWEB system is such a tool which allows to verify and to repair XML web sites instances, against sets of requirements which have to be fulfilled, through abductive reasoning. We define an expressive characterization of rules for checking and repairing web sites' errors and we do a formal mapping of a fragment of a well known XML query language, namely Xcerpt, to abductive logic programs suitable to fed as input to the CIFF proof procedure. Finally, the CIFF proof procedure detects the errors and possibly suggests modifications to the XML instances to repair them. The soundness of this process is directly inherited from the soundness of CIFF

The DLV System for Knowledge Representation and Reasoning

This paper presents the DLV system, which is widely considered the state-of-the-art implementation of disjunctive logic programming, and addresses several aspects. As for problem solving, we provide a formal definition of its kernel language, function-free disjunctive logic programs (also known as disjunctive datalog), extended by weak constraints, which are a powerful tool to express optimization problems. We then illustrate the usage of DLV as a tool for knowledge representation and reasoning, describing a new declarative programming methodology which allows one to encode complex problems (up to $\Delta^P_3$-complete problems) in a declarative fashion. On the foundational side, we provide a detailed analysis of the computational complexity of the language of DLV, and by deriving new complexity results we chart a complete picture of the complexity of this language and important fragments thereof. Furthermore, we illustrate the general architecture of the DLV system which has been influenced by these results. As for applications, we overview application front-ends which have been developed on top of DLV to solve specific knowledge representation tasks, and we briefly describe the main international projects investigating the potential of the system for industrial exploitation. Finally, we report about thorough experimentation and benchmarking, which has been carried out to assess the efficiency of the system. The experimental results confirm the solidity of DLV and highlight its potential for emerging application areas like knowledge management and information integration.Comment: 56 pages, 9 figures, 6 table

Neuere Entwicklungen der deklarativen KI-Programmierung : proceedings

The field of declarative AI programming is briefly characterized. Its recent developments in Germany are reflected by a workshop as part of the scientific congress KI-93 at the Berlin Humboldt University. Three tutorials introduce to the state of the art in deductive databases, the programming language Gödel, and the evolution of knowledge bases. Eleven contributed papers treat knowledge revision/program transformation, types, constraints, and type-constraint combinations