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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
 

Social Software is...


Social Software
Social Software can be thought of as "software which extends, or derives added value from, human social behaviour - message boards, musical taste-sharing, photo-sharing, instant messaging, mailing lists, social networking."

Interacting with other people not only forms the core of human social and psychological experience, but also lies at the centre of what makes the internet such a rich, powerful and exciting collection of knowledge media. We are especially interested in what happens when such interactions take place on a very large scale -- not only because we work regularly with tens of thousands of distance learners at the Open University, but also because it is evident that being part of a crowd in real life possesses a certain 'buzz' of its own, and poses a natural challenge. Different nuances emerge in different user contexts, so we choose to investigate the contexts of work, learning and play to better understand the trade-offs involved in designing effective large-scale social software for multiple purposes.