55 research outputs found
Provenance-based validation of E-science experiments
E-Science experiments typically involve many distributed services maintained by different organisations. After an experiment has been executed, it is useful for a scientist to verify that the execution was performed correctly or is compatible with some existing experimental criteria or standards. Scientists may also want to review and verify experiments performed by their colleagues. There are no existing frameworks for validating such experiments in today's e-Science systems. Users therefore have to rely on error checking performed by the services, or adopt other ad hoc methods. This paper introduces a platform-independent framework for validating workflow executions. The validation relies on reasoning over the documented provenance of experiment results and semantic descriptions of services advertised in a registry. This validation process ensures experiments are performed correctly, and thus results generated are meaningful. The framework is tested in a bioinformatics application that performs protein compressibility analysis
Terminological representation, natural language & relation algebra
In this paper I establish a link between {\sc kl-one}-based knowledge representation concerned with {\em terminological representation} and the work of P. Suppes (1976,1979,1981) and M. B\"ottner (1985,1989) in computational linguistics. I show how this link can be utilised for the problem of finding adequate terminological representations for given information formulated in ordinary English
Attributive Concept Descriptions with Unions and Complements
This paper investigates the consequences of adding unions and complements to the attributive concept descriptions employed in KL-ONE-like knowledge representation languages. It is shown that deciding consistency and subsumption of such descriptions are PSPACE-complete problems that can be decided with linear space
Description Logics Go Second-Order -- Extending EL with Universally Quantified Concepts
The study of Description Logics have been historically mostly focused on
features that can be translated to decidable fragments of first-order logic. In
this paper, we leave this restriction behind and look for useful and decidable
extensions outside first-order logic. We introduce universally quantified
concepts, which take the form of variables that can be replaced with arbitrary
concepts, and define two semantics of this extension. A schema semantics allows
replacements of concept variables only by concepts from a particular language,
giving us axiom schemata similar to modal logics. A second-order semantics
allows replacement of concept variables with arbitrary subsets of the domain,
which is similar to quantified predicates in second-order logic.
To study the proposed semantics, we focus on the extension of the description
logic . We show that for a useful fragment of the extension, the
conclusions entailed by the different semantics coincide, allowing us to use
classical reasoning algorithms even for the second-order
semantics. For a slightly smaller, but still useful, fragment, we were also
able to show polynomial decidability of the extension. This fragment, in
particular, can express a generalized form of role chain axioms, positive self
restrictions, and some forms of (local) role-value-maps from KL-ONE, without
requiring any additional constructors
Decidable Reasoning in Terminological Knowledge Representation Systems
Terminological knowledge representation systems (TKRSs) are tools for
designing and using knowledge bases that make use of terminological languages
(or concept languages). We analyze from a theoretical point of view a TKRS
whose capabilities go beyond the ones of presently available TKRSs. The new
features studied, often required in practical applications, can be summarized
in three main points. First, we consider a highly expressive terminological
language, called ALCNR, including general complements of concepts, number
restrictions and role conjunction. Second, we allow to express inclusion
statements between general concepts, and terminological cycles as a particular
case. Third, we prove the decidability of a number of desirable TKRS-deduction
services (like satisfiability, subsumption and instance checking) through a
sound, complete and terminating calculus for reasoning in ALCNR-knowledge
bases. Our calculus extends the general technique of constraint systems. As a
byproduct of the proof, we get also the result that inclusion statements in
ALCNR can be simulated by terminological cycles, if descriptive semantics is
adopted.Comment: See http://www.jair.org/ for any accompanying file
Role-Value Maps and General Concept Inclusions in the Description Logic FL₀
We investigate the impact that general concept inclusions and role-value maps have on the complexity and decidability of reasoning in the Description Logic FL₀. On the one hand, we give a more direct proof for ExpTimehardness of subsumption w.r.t. general concept inclusions in FL₀. On the other hand, we determine restrictions on role-value maps that ensure decidability of subsumption, but we also show undecidability for the cases where these restrictions are not satisfied
Incorporating generalized quantifiers into description logic for representing data source contents
Title from cover. "January 1998."Includes bibliographical references (p. 19-21).Steven Yi-cheng Tu and Stuart E. Madnick
On subsumption and semiunification in feature algebras
AbstractWe consider a generalization of term subsumption, or matching, to a class of mathematical structures which we call feature algebras. We show how these generalize both first-order terms and the feature structures used in computational linguistics. The notion of term subsumption generalizes to a natural notion of algebra homomorphism. In the setting of feature algebras, unification, corresponds naturally to solving constraints involving equalities between strings of unary function symbols, and semiunification also allows inequalities representing subsumption constraints. Our generalization allows us to show that the semiunification problem for finite feature algebras is undecidable. This implies that the corresponding problem for rational trees (cyclic terms) is also undecidable
A novel framework to improve motion planning of robotic systems through semantic knowledge-based reasoning
The need to improve motion planning techniques for manipulator robots, and new effective strategies to manipulate different objects to perform more complex tasks, is crucial for various real-world applications where robots cooperate with humans. This paper proposes a novel framework that aims to improve the motion planning of a robotic agent (a manipulator robot) through semantic knowledge-based reasoning. The Semantic Web Rule Language (SWRL) was used to infer new knowledge based on the known environment and the robotic system. Ontological knowledge, e.g., semantic maps, were generated through a deep neural network, trained to detect and classify objects in the environment where the robotic agent performs. Manipulation constraints were deduced, and the environment corresponding to the agent’s manipulation workspace was created so the planner could interpret it to generate a collision-free path. For reasoning with the ontology, different SPARQL queries were used. The proposed framework was implemented and validated in a real experimental setup, using the planning framework ROSPlan to perform the planning tasks. The proposed framework proved to be a promising strategy to improve motion planning of robotics systems, showing the benefits of artificial intelligence, for knowledge representation and reasoning in robotics.info:eu-repo/semantics/publishedVersio
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