AGM-Like Paraconsistent Belief Change

Two systems of belief change based on paraconsistent logics are introduced in this article by means of AGM-like postulates. The first one, AGMp, is defined over any paraconsistent logic which extends classical logic such that the law of excluded middle holds w.r.t. the paraconsistent negation. The second one, AGMo , is specifically designed for paraconsistent logics known as Logics of Formal Inconsistency (LFIs), which have a formal consistency operator that allows to recover all the classical inferences. Besides the three usual operations over belief sets, namely expansion, contraction and revision (which is obtained from contraction by the Levi identity), the underlying paraconsistent logic allows us to define additional operations involving (non-explosive) contradictions. Thus, it is defined external revision (which is obtained from contraction by the reverse Levi identity), consolidation and semi-revision, all of them over belief sets. It is worth noting that the latter operations, introduced by S. Hansson, involve the temporary acceptance of contradictory beliefs, and so they were originally defined only for belief bases. Unlike to previous proposals in the literature, only defined for specific paraconsistent logics, the present approach can be applied to a general class of paraconsistent logics which are supraclassical, thus preserving the spirit of AGM. Moreover, representation theorems w.r.t. constructions based on selection functions are obtained for all the operations

An agent-oriented approach to change propagation in software evolution

Software maintenance and evolution are inevitable activities since almost all software that is useful and successful stimulates user-generated requests for change and improvements. One of the most critical problems in software maintenance and evolution is to maintain consistency between software artefacts by propagating changes correctly. Although many approaches have been proposed, automated change propagation is still a significant technical challenge in software engineering. In this paper we present a novel, agent-oriented approach to deal with change propagation in evolving software systems that are developed using the Prometheus methodology. A metamodel with a set of the Object Constraint Language (OCL) rules forms the basis of the proposed framework. The underlying change propagation mechanism of our framework is based on the well-known Belief-Desire-Intention (BDI) agent architecture. Traceability information and design heuristics are also incorporated into the framework to facilitate the change propagation process

IT Management Using a Heavyweight CIM Ontology

This paper presents an approach for ontology-based IT management based on a heavyweight (formal) ontology using the Web Ontology Language (OWL). The ontology comprises a complete OWL representation of the Common Information Model (CIM) and management rules defined in the Semantic Web Rule Language (SWRL). The ontology not only models the managed system types, but a runtime system dynamically updates model instances in the ontology that reflect values of managed system entities. This allows the evalution of rules that take into account both model and model instances. A reaction module uses the CIM interface of the managed system to invoke CIM methods according to rule evaluation results, thus resulting in automated management. In order to ensure the consistency of the ontology when changes are performed, belief change theory is employed

Supporting software evolution in agent systems

Software maintenance and evolution is arguably a lengthy and expensive phase in the life cycle of a software system. A critical issue at this phase is change propagation: given a set of primary changes that have been made to software, what additional secondary changes are needed to maintain consistency between software artefacts? Although many approaches have been proposed, automated change propagation is still a significant technical challenge in software maintenance and evolution. Our objective is to provide tool support for assisting designers in propagating changes during the process of maintaining and evolving models. We propose a novel, agent-oriented, approach that works by repairing violations of desired consistency rules in a design model. Such consistency constraints are specified using the Object Constraint Language (OCL) and the Unified Modelling Language (UML) metamodel, which form the key inputs to our change propagation framework. The underlying change propagation mechanism of our framework is based on the well-known Belief-Desire-Intention (BDI) agent architecture. Our approach represents change options for repairing inconsistencies using event-triggered plans, as is done in BDI agent platforms. This naturally reflects the cascading nature of change propagation, where each change (primary or secondary) can require further changes to be made. We also propose a new method for generating repair plans from OCL consistency constraints. Furthermore, a given inconsistency will typically have a number of repair plans that could be used to restore consistency, and we propose a mechanism for semi-automatically selecting between alternative repair plans. This mechanism, which is based on a notion of cost, takes into account cascades (where fixing the violation of a constraint breaks another constraint), and synergies between constraints (where fixing the violation of a constraint also fixes another violated constraint). Finally, we report on an evaluation of the approach, covering both effectiveness and efficiency

Datalog± Ontology Consolidation

Knowledge bases in the form of ontologies are receiving increasing attention as they allow to clearly represent both the available knowledge, which includes the knowledge in itself and the constraints imposed to it by the domain or the users. In particular, Datalog ± ontologies are attractive because of their property of decidability and the possibility of dealing with the massive amounts of data in real world environments; however, as it is the case with many other ontological languages, their application in collaborative environments often lead to inconsistency related issues. In this paper we introduce the notion of incoherence regarding Datalog± ontologies, in terms of satisfiability of sets of constraints, and show how under specific conditions incoherence leads to inconsistent Datalog ± ontologies. The main contribution of this work is a novel approach to restore both consistency and coherence in Datalog± ontologies. The proposed approach is based on kernel contraction and restoration is performed by the application of incision functions that select formulas to delete. Nevertheless, instead of working over minimal incoherent/inconsistent sets encountered in the ontologies, our operators produce incisions over non-minimal structures called clusters. We present a construction for consolidation operators, along with the properties expected to be satisfied by them. Finally, we establish the relation between the construction and the properties by means of a representation theorem. Although this proposal is presented for Datalog± ontologies consolidation, these operators can be applied to other types of ontological languages, such as Description Logics, making them apt to be used in collaborative environments like the Semantic Web.Fil: Deagustini, Cristhian Ariel David. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Martinez, Maria Vanina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Falappa, Marcelo Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Simari, Guillermo Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentin

An Architectural Approach to Ensuring Consistency in Hierarchical Execution

Hierarchical task decomposition is a method used in many agent systems to organize agent knowledge. This work shows how the combination of a hierarchy and persistent assertions of knowledge can lead to difficulty in maintaining logical consistency in asserted knowledge. We explore the problematic consequences of persistent assumptions in the reasoning process and introduce novel potential solutions. Having implemented one of the possible solutions, Dynamic Hierarchical Justification, its effectiveness is demonstrated with an empirical analysis