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Volume 9 / Issue 6

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DOI:   10.3217/jucs-009-06-0551

 

Towards the Semantic Grid: Putting Knowledge to Work in Design Optimisation

Feng Tao (Department of Electronics and Computer Science, University of Southampton, UK)

Liming Chen (Department of Electronics and Computer Science, University of Southampton, UK)

Nigel Shadbolt (Department of Electronics and Computer Science, University of Southampton, UK)

Graeme Pound (School of Engineering Sciences, University of Southampton, UK)

Simon Cox (School of Engineering Sciences, University of Southampton, UK)

Abstract: Modern computational Problem Solving Environments (PSEs) become more and more complex and knowledge intensive in terms of their integrated toolsets, in particular for engineering design search and optimization. Whether these toolsets can be assembled effectively to produce satisfactory results depends heavily on using the best domain practice and following decisions made by skilled engineers in practical situations. In this paper, a knowledge based approach is used to acquire this knowledge from existing sources and model it in a maintainable fashion. Ontologies are used to develop the conceptualization of a knowledge base. In order to reuse this knowledge to provide guidance at knowledge intensive points, we propose a knowledge based advisor, which can give a context-aware critique to guide users through effective operations of building domain workflows. The concept of a state panel is proposed to collect system state information, which is then reasoned about together with various task models in the JESS (Java Expert System Shell) environment. Two reasoning strategies are designed for different advising styles. A multilayer and client-server style architecture is proposed to illustrate how this advisor can be deployed to make available its knowledge advising service to a real workflow construction PSE in a maintainable fashion. Throughout we use the example of these knowledge services in the context of design optimization in engineering.

Keywords: JESS, XML, knowledge base, knowledge engineering, ontology, production rules, workflow planning

Categories: I.2.5