By Daniel J. Clancy PhD (auth.), Ann Macintosh BSc, CEng, Mike Moulton BSc, Frans Coenen PhD (eds.)
Ann Macintosh Napier college, united kingdom The papers during this quantity are the refereed software papers offered at ES2000, the 20th SGES overseas convention on wisdom dependent platforms and utilized man made Intelligence, held in Cambridge in December 2000. The scope of the appliance papers has elevated over fresh years to hide not only cutting edge purposes utilizing conventional wisdom dependent platforms, but in addition to incorporate functions demonstrating the full variety of AI applied sciences. This quantity comprises 13 refereed papers describing deployed purposes or rising functions, including an invited keynote paper by way of Dr. Daniel Clancy of NASA Ames examine Centre. The papers have been topic to refereeing through not less than "expert" referees. All papers which have been debatable for a few cause have been mentioned intensive via the appliance Programme Committee. For the applying move, a paper is suitable no matter if it describes a process which has no longer but been put in, supplied the applying is unique and the paper discusses the types of items that may support others wanting to resolve the same challenge. Papers were chosen to spotlight serious parts of good fortune (and failure) and to offer the advantages and classes learnt to different builders. Papers this 12 months conceal subject matters as varied as: KBS for protecting offshore structures; info Mining to foretell company company failure; built-in AI suggestions to help box carrier engineers; usual Language utilized to the knowledge safeguard Act; wisdom administration and the appliance of neural networks.
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Additional info for Applications and Innovations in Intelligent Systems VIII: Proceedings of ES2000, the Twentieth SGES International Conference on Knowledge Based Systems and Applied Artificial Intelligence, Cambridge, December 2000
1 but it does go part way towards this. 3 Attaching parameters to Knowledge Nodes Interviews are used as the main vehicle in the construction of structural knowledge maps. During interviews, people are asked to provide information about the structure of knowledge in the domain in question. There are many possibilities as to what this information should be and of course an acknowledgement that interviewees will often need to estimate answers based on their own experience. Several parameters and combinations of parameters have been tested and the following four have been found to be the most useful in all audits.
However, the concepts of mouse movement and related pointer movement and button clicking would be meaningless without the prior knowledge of how to use a mouse. Learning dependency is a human centred approach to mapping the structure of knowledge. Learning dependency means that it is necessary to know knowledge 'Y' before knowledge 'X' can be fully known. Learning dependency also provides at least some encouragement that it is really knowledge that is being managed. The dependency structure, as used when acquiring expert knowledge, provides some justification as to truth value.
Milne R. L. Smith C. Knowledge Management Guidelines. NWAIAG Publication. 1998. L. Smith C. Scott S. McBriar I, Walbank S. Bain G. Unsworth P. L. Creating Knowledge Maps by Exploiting Dependent Relationships in Applications and Innovations in Intelligent Systems VII, Eds Ellis, Moulton & Coenen, Springer, 1999 pp 63-78 Graham I, Llewelyn Jones P. Expert Systems Knowledge Uncertainty and Decision. Chapman and Hall 1988 pp 20-23 Sosa E, Jaegwon K. Epistemology An Anthology. F. 1984. Conceptual Structures: Information Processing in Mind and Machine.
Applications and Innovations in Intelligent Systems VIII: Proceedings of ES2000, the Twentieth SGES International Conference on Knowledge Based Systems and Applied Artificial Intelligence, Cambridge, December 2000 by Daniel J. Clancy PhD (auth.), Ann Macintosh BSc, CEng, Mike Moulton BSc, Frans Coenen PhD (eds.)