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Tech Report kmi-97-14 Abstract


Understanding Evolutionary Computing: A hands on approach
Techreport ID: kmi-97-14
Date: 1997
Author(s): Trevor Collins
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Evolutionary computing is the study of robust search algorithms based on the principles of evolution. An Evolutionary Algorithm (EA) searches a problem space in order to find possible solutions to a given problem. This paper is intended to highlight the advantages of using software visualization techniques in evolutionary computing: Firstly it describes how a high-dimensional problem space can be represented in two (or more) dimensions, suitable for visualization; secondly it introduces how EA designers can use this visualization to explore their algorithm's search behavior in the problem space; and thirdly, it explores how this "hands on" approach can be extended to the evolutionary process, in order to improve an algorithm's performance.
 
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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.