12,328 research outputs found
Multi-Paradigm Reasoning for Access to Heterogeneous GIS
Accessing and querying geographical data in a uniform way has become easier in recent years. Emerging standards like WFS turn
the web into a geospatial web services enabled place. Mediation
architectures like VirGIS overcome syntactical and semantical heterogeneity
between several distributed sources. On mobile devices,
however, this kind of solution is not suitable, due to limitations,
mostly regarding bandwidth, computation power, and available storage
space. The aim of this paper is to present a solution for providing
powerful reasoning mechanisms accessible from mobile applications
and involving data from several heterogeneous sources.
By adapting contents to time and location, mobile web information
systems can not only increase the value and suitability of the
service itself, but can substantially reduce the amount of data delivered
to users. Because many problems pertain to infrastructures
and transportation in general and to way finding in particular, one
cornerstone of the architecture is higher level reasoning on graph
networks with the Multi-Paradigm Location Language MPLL. A
mediation architecture is used as a āgraph providerā in order to
transfer the load of computation to the best suited component ā
graph construction and transformation for example being heavy on
resources. Reasoning in general can be conducted either near the
āsourceā or near the end user, depending on the specific use case.
The concepts underlying the proposal described in this paper are
illustrated by a typical and concrete scenario for web applications
A formal support to business and architectural design for service-oriented systems
Architectural Design Rewriting (ADR) is an approach for the design of software architectures developed within Sensoria by reconciling graph transformation and process calculi techniques. The key feature that makes ADR a suitable and expressive framework is the algebraic handling of structured graphs, which improves the support for specification, analysis and verification of service-oriented architectures and applications. We show how ADR is used as a formal ground for high-level modelling languages and approaches developed within Sensoria
A Graphical Language for Proof Strategies
Complex automated proof strategies are often difficult to extract, visualise,
modify, and debug. Traditional tactic languages, often based on stack-based
goal propagation, make it easy to write proofs that obscure the flow of goals
between tactics and are fragile to minor changes in input, proof structure or
changes to tactics themselves. Here, we address this by introducing a graphical
language called PSGraph for writing proof strategies. Strategies are
constructed visually by "wiring together" collections of tactics and evaluated
by propagating goal nodes through the diagram via graph rewriting. Tactic nodes
can have many output wires, and use a filtering procedure based on goal-types
(predicates describing the features of a goal) to decide where best to send
newly-generated sub-goals.
In addition to making the flow of goal information explicit, the graphical
language can fulfil the role of many tacticals using visual idioms like
branching, merging, and feedback loops. We argue that this language enables
development of more robust proof strategies and provide several examples, along
with a prototype implementation in Isabelle
Towards Analytics Aware Ontology Based Access to Static and Streaming Data (Extended Version)
Real-time analytics that requires integration and aggregation of
heterogeneous and distributed streaming and static data is a typical task in
many industrial scenarios such as diagnostics of turbines in Siemens. OBDA
approach has a great potential to facilitate such tasks; however, it has a
number of limitations in dealing with analytics that restrict its use in
important industrial applications. Based on our experience with Siemens, we
argue that in order to overcome those limitations OBDA should be extended and
become analytics, source, and cost aware. In this work we propose such an
extension. In particular, we propose an ontology, mapping, and query language
for OBDA, where aggregate and other analytical functions are first class
citizens. Moreover, we develop query optimisation techniques that allow to
efficiently process analytical tasks over static and streaming data. We
implement our approach in a system and evaluate our system with Siemens turbine
data
The System Kato: Detecting Cases of Plagiarism for Answer-Set Programs
Plagiarism detection is a growing need among educational institutions and
solutions for different purposes exist. An important field in this direction is
detecting cases of source-code plagiarism. In this paper, we present the tool
Kato for supporting the detection of this kind of plagiarism in the area of
answer-set programming (ASP). Currently, the tool is implemented for DLV
programs but it is designed to handle other logic-programming dialects as well.
We review the basic features of Kato, introduce its theoretical underpinnings,
and discuss an application of Kato for plagiarism detection in the context of
courses on logic programming at the Vienna University of Technology
Progress in AI Planning Research and Applications
Planning has made significant progress since its inception in the 1970s, in terms both of the efficiency and sophistication of its algorithms and representations and its potential for application to real problems. In this paper we sketch the foundations of planning as a sub-field of Artificial Intelligence and the history of its development over the past three decades. Then some of the recent achievements within the field are discussed and provided some experimental data demonstrating the progress that has been made in the application of general planners to realistic and complex problems. The paper concludes by identifying some of the open issues that remain as important challenges for future research in planning
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