The paradigm of argumentation has been used in the literature to assign meaning to knowledge bases in general, and logic programs in particu lar. With this paradigm, rules of logic program are viewed as encoding argume nts of an agent, and the meaning of the program is determined by those argumen ts that somehow (depending on the specific semantics) can defend themselves from the attacks of others arguments, named acceptable arguments. In previou s work we presented an argumentation based declarative semantics allowing parac onsistent reasoning and also dealing with sets of logic programs that argue and coo perate among each other. In this paper we focus on the properties of this seman tics in what regards paraconsistency and propose a procedure for prov ing an argument according to that semantics.

methods

Logic programs with classical negation

Argumentation-based Proof for an Argument in a Paraconsistent Setting

Power systems are naturally exposed to several fault conditions, namely short-circuits. Automatic protection and control systems are responsible for selective tripping of faulted devices and their subsequent reconnection.

An application to automatically diagnosing abnormal conditions in power distribution network substations is described in this work. It is based on a model of the power network and the associated protection and control system. Its main purpose is to assist in the analysis of protection device records, explain the observed operations and detect possible misbehavior. This application is specified and implemented using a combination of Logic Programming tools and techniques, in particular non-monotonic reasoning. The model is structured in several abstraction levels and a set of strategies and preferences is used to guide the diagnosis process.

The developed application was tested with several substation configurations, including sequences of events recorded at real installations.

Diagnosis of power system protection

Entity resolution (ER) is an important problem in data cleaning. It is about iden- tifying and merging records in a database that represent the same external entity. Relatively recently, declarative rules called matching dependencies (MDs) have been proposed for specifying similarity conditions under which attribute values in database records are merged. An ER process supported by MDs over a dirty instance may lead to multiple clean instances.
In this thesis, we first present disjunctive answer set programs that capture through their models the class of alternative clean instances obtained after an ER process based on MDs. With these programs, we can obtain clean answers to queries by skeptically reasoning from the program. As an important practical case of ER, we provide a declarative reconstruction of the so-called union-case ER methodology, as presented through a generic approach to ER, the so-called Swoosh approach. We extend our ASP-based account of the union-case of Swoosh with negative rules.
In this work, we extend MDs to relational MDs, which capture more application semantics, and identify classes of relational MDs for which the proposed declarative specifications for ER via MDs can be automatically rewritten into stratified Datalog programs.
We also show the process and the benefits of integrating four components of ER: (a) Building a classifier for duplicate/non-duplicate record pairs using machine learn- ing (ML) techniques; (b) Use of relational MDs for supporting the blocking phase of ML; (c) Record merging on the basis of the classifier results; and (d) The use of the declarative language LogiQL -an extended form of Datalog supported by the LogicBlox platform- for all activities related to data processing, and the specification and enforcement of MDs.

/pdf/declarative-entity-resolution-via-matching-dependencies-and-2rrfzom7ci.pdf

Declarative Entity Resolution Via Matching Dependencies and Combining Matching Dependencies With Machine Learning for Entity Resolution

We propose to extend the language of extended logic programs by providing a declarative semantics for the use of sets as terms. Such an extension is intuitively natural, since humans frequently reason about collections of items. Our approach to defining a declarative semantics for sets differs from other approaches in that other approaches are very limited in their use of negation, and our approach is model-theoretic in a context allowing multiple models. Further, our approach is based on the answer set semantics, providing a well understood foundation. The language defined here can represent a wide range of common sense problems. As a side effect, an auxiliary contribution of this work is that a subset of this work provides a declarative semantics for how the setof symbol and how sets as terms should be and can be implemented in Prolog..

/pdf/set-semantics-and-operations-based-upon-answer-set-semantics-2bfol8i525.pdf

Logic programs with classical negation

Citations

Argumentation-based Proof for an Argument in a Paraconsistent Setting

Diagnosis of power system protection

Declarative Entity Resolution Via Matching Dependencies and Combining Matching Dependencies With Machine Learning for Entity Resolution

Set Semantics and Operations Based Upon Answer Set Semantics

Multimodal Nonmonotonic Logics of Minimal Knowledge.

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