104,473 research outputs found
A Goal-Directed Implementation of Query Answering for Hybrid MKNF Knowledge Bases
Ontologies and rules are usually loosely coupled in knowledge representation
formalisms. In fact, ontologies use open-world reasoning while the leading
semantics for rules use non-monotonic, closed-world reasoning. One exception is
the tightly-coupled framework of Minimal Knowledge and Negation as Failure
(MKNF), which allows statements about individuals to be jointly derived via
entailment from an ontology and inferences from rules. Nonetheless, the
practical usefulness of MKNF has not always been clear, although recent work
has formalized a general resolution-based method for querying MKNF when rules
are taken to have the well-founded semantics, and the ontology is modeled by a
general oracle. That work leaves open what algorithms should be used to relate
the entailments of the ontology and the inferences of rules. In this paper we
provide such algorithms, and describe the implementation of a query-driven
system, CDF-Rules, for hybrid knowledge bases combining both (non-monotonic)
rules under the well-founded semantics and a (monotonic) ontology, represented
by a CDF Type-1 (ALQ) theory. To appear in Theory and Practice of Logic
Programming (TPLP
COLAB : a hybrid knowledge representation and compilation laboratory
Knowledge bases for real-world domains such as mechanical engineering require expressive and efficient representation and processing tools. We pursue a declarative-compilative approach to knowledge engineering. While Horn logic (as implemented in PROLOG) is well-suited for representing relational clauses, other kinds of declarative knowledge call for hybrid extensions: functional dependencies and higher-order knowledge should be modeled directly. Forward (bottom-up) reasoning should be integrated with backward (top-down) reasoning. Constraint propagation should be used wherever possible instead of search-intensive resolution. Taxonomic knowledge should be classified into an intuitive subsumption hierarchy. Our LISP-based tools provide direct translators of these declarative representations into abstract machines such as an extended Warren Abstract Machine (WAM) and specialized inference engines that are interfaced to each other. More importantly, we provide source-to-source transformers between various knowledge types, both for user convenience and machine efficiency. These formalisms with their translators and transformers have been developed as part of COLAB, a compilation laboratory for studying what we call, respectively, "vertical\u27; and "horizontal\u27; compilation of knowledge, as well as for exploring the synergetic collaboration of the knowledge representation formalisms. A case study in the realm of mechanical engineering has been an important driving force behind the development of COLAB. It will be used as the source of examples throughout the paper when discussing the enhanced formalisms, the hybrid representation architecture, and the compilers
Combining open and closed world reasoning for the semantic web
Dissertação para obtenção do Grau de Doutor
em InformáticaOne important problem in the ongoing standardization of knowledge representation
languages for the Semantic Web is combining open world ontology languages, such as the OWL-based ones, and closed world rule-based languages.
The main difficulty of such a combination is that both formalisms are quite orthogonal w.r.t. expressiveness and how decidability is achieved. Combining non-monotonic rules and ontologies is thus a challenging task
that requires careful balancing between expressiveness of the knowledge representation language and the computational complexity of reasoning.
In this thesis, we will argue in favor of a combination of ontologies and nonmonotonic
rules that tightly integrates the two formalisms involved, that has a computational complexity that is as low as possible, and that allows us to query for information instead of calculating the whole model. As our starting point we choose the mature approach of hybrid MKNF knowledge
bases, which is based on an adaptation of the Stable Model Semantics to knowledge bases consisting of ontology axioms and rules. We extend the two-valued framework of MKNF logics to a three-valued logics, and we propose a well-founded semantics for non-disjunctive hybrid MKNF knowledge bases. This new semantics promises to provide better efficiency of reasoning,and it is faithful w.r.t. the original two-valued MKNF semantics and compatible with both the OWL-based semantics and the traditional Well-
Founded Semantics for logic programs. We provide an algorithm based on operators to compute the unique model, and we extend SLG resolution with tabling to a general framework that allows us to query a combination of non-monotonic rules and any given ontology language. Finally, we
investigate concrete instances of that procedure w.r.t. three tractable ontology
languages, namely the three description logics underlying the OWL 2 pro les.Fundação para a Ciência e Tecnologia - grant contract SFRH/BD/28745/200
Development of a Multi-agent Collision Resolution System at the Supply of Spare Parts and Components to the Production Equipment of Industrial Enterprises
The approach to the creation of computer facilities for the automation of the technical maintenance of production equipment (TMPE) at industrial enterprises (IE) is outlined. Meaningful and formal statement of the problem of forming solutions for identifying and eliminating collisions that arise when delivering spare parts and components for TMPE are presented. The method of formation of coordinating decisions on maintenance with spare parts and accessories for carrying out TMPE at IE is described. The organization of intellectual support of formation of coordinating decisions by recognition of potential collision in the TMPE process is offered. This procedure involves checking the real existence of the collision and issuing a coordinating decision. In this case, the decision is formed in the event of a disagreement between the need for spare parts and components for the TMPE maintenance, with their availability in the PP warehouse. The ways of software implementation of this method in the environment of multi-agent system are considered. In particular, the description of the multi-agent system developed during the prototype research is given. The prototype is implemented using CORBA technology, in accordance with DSTU ISO/ EC 2382-15:2005. The calculation of the efficiency of the application of the developed computer tools in production is shown. To assess the quality of the system, a sliding control method based on leave-on-out cross-validation (LOOCV) is applied
Rosetta Brains: A Strategy for Molecularly-Annotated Connectomics
We propose a neural connectomics strategy called Fluorescent In-Situ
Sequencing of Barcoded Individual Neuronal Connections (FISSEQ-BOINC),
leveraging fluorescent in situ nucleic acid sequencing in fixed tissue
(FISSEQ). FISSEQ-BOINC exhibits different properties from BOINC, which relies
on bulk nucleic acid sequencing. FISSEQ-BOINC could become a scalable approach
for mapping whole-mammalian-brain connectomes with rich molecular annotations
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