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Tech Report kmi-95-09 Abstract


Solving VT in VITAL: A Study in Model Construction and Knowledge Reuse
Techreport ID: kmi-95-09
Date: 1995
Author(s): Enrico Motta, *Kieron O'Hara, *Nigel Shadbolt, Arthur Stutt and Zdenek Zdrahal
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In this paper we discuss a solution to the Sisyphus II elevator design problem developed using the VITAL approach to structured knowledge-based system development. In particular we illustrate in detail the process by which an initial model of Propose&Revise problem solving was constructed using a generative grammar of model fragments and then refined and operationalised in the VITAL operational conceptual modelling language (OCML). In the paper we also discuss in detail the properties of a particular Propose&Revise architecture, called 'Complete-Model-then-Revise', and we show that it compares favourably in terms of competence with alternative Propose&Revise models. Moreover, using as an example the VT domain ontology provided as part of the Sisyphus II task, we critically examine the issues affecting the development of reusable ontologies. Finally, we discuss the performance of our problem solver and we show how we can use machine learning techniques to uncover additional strategic knowledge not present in the VT domain. *Artificial Intelligence Group, Dept. of Psychology, University of Nottingham University Park, Nottingham, NG7 2RD. U.K. nrs@psychology.nottingham.ac.uk The VITAL project is a 4.5 year research and development enterprise involving seven organisations drawn from four countries. The total effort invested is about 80 man-years. VITAL is partially funded by the ESPRIT Program of the Commision of the European Communities, as project number 5365. The partners in the VITAL project are the following: Syseca Temps Reel (F), Bull Cediag (F), Onera (F), The Open University (UK), University of Nottingham (UK), University of Helsinki (SF), and Andersen Consulting (E).

Publication(s):

International Journal of Human-Computer Studies, Special Issue on the VT Elevator Design Problem. Vol. 44 (3-4). March-April 1996.
 
KMi Publications Event | SSSW 2013, The 10th Summer School on Ontology Engineering and the Semantic Web Journal | 25 years of knowledge acquisition
 

Semantic Web and Knowledge Services is...


Semantic Web and Knowledge Services
"The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation" (Berners-Lee et al., 2001).

Our research in the Semantic Web area looks at the potentials of fusing together advances in a range of disciplines, and applying them in a systemic way to simplify the development of intelligent, knowledge-based web services and to facilitate human access and use of knowledge available on the web. For instance, we are exploring ways in which tnatural language interfaces can be used to facilitate access to data distributed over different repositories. We are also developing infrastructures to support rapid development and deployment of semantic web services, which can be used to create web applications on-the-fly. We are also investigating ways in which semantic technology can support learning on the web, through a combination of knowledge representation support, pedagogical theories and intelligent content aggregation mechanisms. Finally, we are also investigating the Semantic Web itself as a domain of analysis and performing large scale empirical studies to uncover data about the concrete epistemologies which can be found on the Semantic Web. This exciting new area of research gives us concrete insights on the different conceptualizations that are present on the Semantic Web by giving us the possibility to discover which are the most common viewpoints, which viewpoints are mutually inconsistent, to what extent different models agree or disagree, etc...

Our aim is to be at the forefront of both theoretical and practical developments on the Semantic Web not only by developing theories and models, but also by building concrete applications, for a variety of domains and user communities, including KMi and the Open University itself.