Using Methods of Declarative Logic Programming for Intelligent Information Agents

The search for information on the web is faced with several problems, which arise on the one hand from the vast number of available sources, and on the other hand from their heterogeneity. A promising approach is the use of multi-agent systems of information agents, which cooperatively solve advanced information-retrieval problems. This requires capabilities to address complex tasks, such as search and assessment of sources, query planning, information merging and fusion, dealing with incomplete information, and handling of inconsistency. In this paper, our interest is in the role which some methods from the field of declarative logic programming can play in the realization of reasoning capabilities for information agents. In particular, we are interested in how they can be used and further developed for the specific needs of this application domain. We review some existing systems and current projects, which address information-integration problems. We then focus on declarative knowledge-representation methods, and review and evaluate approaches from logic programming and nonmonotonic reasoning for information agents. We discuss advantages and drawbacks, and point out possible extensions and open issues.Comment: 66 pages, 1 figure, to be published in "Theory and Practice of Logic Programming

Coherent Integration of Databases by Abductive Logic Programming

We introduce an abductive method for a coherent integration of independent data-sources. The idea is to compute a list of data-facts that should be inserted to the amalgamated database or retracted from it in order to restore its consistency. This method is implemented by an abductive solver, called Asystem, that applies SLDNFA-resolution on a meta-theory that relates different, possibly contradicting, input databases. We also give a pure model-theoretic analysis of the possible ways to `recover' consistent data from an inconsistent database in terms of those models of the database that exhibit as minimal inconsistent information as reasonably possible. This allows us to characterize the `recovered databases' in terms of the `preferred' (i.e., most consistent) models of the theory. The outcome is an abductive-based application that is sound and complete with respect to a corresponding model-based, preferential semantics, and -- to the best of our knowledge -- is more expressive (thus more general) than any other implementation of coherent integration of databases

Logical Foundations and Complexity of 4QL, a Query Language with Unrestricted Negation

The paper discusses properties of a DATALOG$^{\neg\neg}$-like query language 4QL, originally outlined in [MS10]. Negated literals in heads of rules naturally lead to inconsistencies. On the other hand, rules do not have to attach meaning to some literals. Therefore 4QL is founded on a four-valued semantics, employing the logic introduced in [MSV08, VMS09] with truth values: 'true', 'false', 'inconsistent' and 'unknown'. 4QL allows one to use rules with negation in heads and bodies of rules, it is based on a simple and intuitive semantics and provides uniform tools for "lightweight" versions of known forms of nonmonotonic reasoning. In addition, 4QL is tractable as regards its data complexity and captures PTIME queries. Even if DATALOG$^{\neg\neg}$ is known as a concept for the last 30 years, to our best knowledge no existing approach enjoys these properties. In the current paper we: - investigate properties of well-supported models of 4QL - prove the correctness of the algorithm for computing well-supported models - show that 4QL has PTIME data complexity and captures PTIME

Confidentiality-Preserving Data Publishing for Credulous Users by Extended Abduction

Publishing private data on external servers incurs the problem of how to avoid unwanted disclosure of confidential data. We study a problem of confidentiality in extended disjunctive logic programs and show how it can be solved by extended abduction. In particular, we analyze how credulous non-monotonic reasoning affects confidentiality.Comment: Paper appears in the Proceedings of the 19th International Conference on Applications of Declarative Programming and Knowledge Management (INAP 2011

An Abductive Framework For Computing Knowledge Base Updates

This paper introduces an abductive framework for updating knowledge bases represented by extended disjunctive programs. We first provide a simple transformation from abductive programs to update programs which are logic programs specifying changes on abductive hypotheses. Then, extended abduction, which was introduced by the same authors as a generalization of traditional abduction, is computed by the answer sets of update programs. Next, different types of updates, view updates and theory updates are characterized by abductive programs and computed by update programs. The task of consistency restoration is also realized as special cases of these updates. Each update problem is comparatively assessed from the computational complexity viewpoint. The result of this paper provides a uniform framework for different types of knowledge base updates, and each update is computed using existing procedures of logic programming.Comment: Appeared in Theory and Practice of Logic Programming, vol. 3, no. 6, 200

Enhancing the expressive power of the U-Datalog language

U-Datalog has been developed with the aim of providing a set-oriented logical update language, guaranteeing update parallelism in the context of a Datalog-like language. In U-Datalog, updates are expressed by introducing constraints (+p(X), to denote insertion, and [minus sign]p(X), to denote deletion) inside Datalog rules. A U-Datalog program can be interpreted as a CLP program. In this framework, a set of updates (constraints) is satisfiable if it does not represent an inconsistent theory, that is, it does not require the insertion and the deletion of the same fact. This approach resembles a very simple form of negation. However, on the other hand, U-Datalog does not provide any mechanism to explicitly deal with negative information, resulting in a language with limited expressive power. In this paper, we provide a semantics, based on stratification, handling the use of negated atoms in U-Datalog programs, and we show which problems arise in defining a compositional semantics.Comment: Appeared in Theory and Practice of Logic Programming, vol. 1, no. 1, 200

Analyzing Graph Transformation Systems through Constraint Handling Rules

Graph transformation systems (GTS) and constraint handling rules (CHR) are non-deterministic rule-based state transition systems. CHR is well-known for its powerful confluence and program equivalence analyses, for which we provide the basis in this work to apply them to GTS. We give a sound and complete embedding of GTS in CHR, investigate confluence of an embedded GTS, and provide a program equivalence analysis for GTS via the embedding. The results confirm the suitability of CHR-based program analyses for other formalisms embedded in CHR.Comment: 45 pages, 11 figures, to appear in Theory and Practice of Logic Programming (TPLP

Linear Models of Computation and Program Learning

We consider two classes of computations which admit taking linear combinations of execution runs: probabilistic sampling and generalized animation. We argue that the task of program learning should be more tractable for these architectures than for conventional deterministic programs. We look at the recent advances in the "sampling the samplers" paradigm in higher-order probabilistic programming. We also discuss connections between partial inconsistency, non-monotonic inference, and vector semantics.Comment: 13 pages; September 3, 2015 version; to appear in the Proceedings of GCAI 2015, Tbilisi, Georgia, Oct.16-18, 201

Reduction of Many-valued into Two-valued Modal Logics

In this paper we develop a 2-valued reduction of many-valued logics, into 2-valued multi-modal logics. Such an approach is based on the contextualization of many-valued logics with the introduction of higher-order Herbrand interpretation types, where we explicitly introduce the coexistence of a set of algebraic truth values of original many-valued logic, transformed as parameters (or possible worlds), and the set of classic two logic values. This approach is close to the approach used in annotated logics, but offers the possibility of using the standard semantics based on Herbrand interpretations. Moreover, it uses the properties of the higher-order Herbrand types, as their fundamental nature is based on autoreferential Kripke semantics where the possible worlds are algebraic truth-values of original many-valued logic. This autoreferential Kripke semantics, which has the possibility of flattening higher-order Herbrand interpretations into ordinary 2-valued Herbrand interpretations, gives us a clearer insight into the relationship between many-valued and 2-valued multi-modal logics. This methodology is applied to the class of many-valued Logic Programs, where reduction is done in a structural way, based on the logic structure (logic connectives) of original many-valued logics. Following this, we generalize the reduction to general structural many-valued logics, in an abstract way, based on Suszko's informal non-constructive idea. In all cases, by using developed 2-valued reductions we obtain a kind of non truth-valued modal meta-logics, where two-valued formulae are modal sentences obtained by application of particular modal operators to original many-valued formulae.Comment: 27 page

AppLP: A Dialogue on Applications of Logic Programming

This document describes the contributions of the 2016 Applications of Logic Programming Workshop (AppLP), which was held on October 17 and associated with the International Conference on Logic Programming (ICLP) in Flushing, New York City.Comment: David S. Warren and Yanhong A. Liu (Editors). 33 pages. Including summaries by Christopher Kane and abstracts or position papers by M. Aref, J. Rosenwald, I. Cervesato, E.S.L. Lam, M. Balduccini, J. Lobo, A. Russo, E. Lupu, N. Leone, F. Ricca, G. Gupta, K. Marple, E. Salazar, Z. Chen, A. Sobhi, S. Srirangapalli, C.R. Ramakrishnan, N. Bj{\o}rner, N.P. Lopes, A. Rybalchenko, and P. Tara