Titlebook: Microcomputers in Medicine; P. D. Coleridge Smith (Senior Lecturer in Surgical Conference proceedings 1988 Springer-Verlag Berlin Heidelbe

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Obstreperous

J. D. Holdsworths for which the KBS gives an incorrect solution. These tools generally employ greedy hill climbing to search the space of possible refinements. Typically refinement algorithms are iterative and at each iteration chooses a fix having the best impact on the faulty KBS. This impact is ascertained by an

GRAZE

S. J. Nixons of these programs will share some of the knowledge they need to carry out their tasks. If there was a way in which this knowledge could be structured and stored in a repository so that it would be easy to browse, then some of these knowledge components could be reused to specify new intelligent sy

周年紀(jì)念日

J. R. Coughlan,M. J. Taylor,W. A. Corbett,R. Shieldss for which the KBS gives an incorrect solution. These tools generally employ greedy hill climbing to search the space of possible refinements. Typically refinement algorithms are iterative and at each iteration chooses a fix having the best impact on the faulty KBS. This impact is ascertained by an

進(jìn)步

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S. L. Smith,M. C. Fairhurst,S. W. Kelly,J. S. R. Baxter Conference on Knowledge Based Systems and Applied ArtifIcial Intelligence, held in Cambridge in December 200 l, together with an invited keynote paper by Professor Derek Sleeman. The conference was organised by SGES, the British Computer Society Specialist Group on Knowledge Based Systems and Appli

intercede

S. Stock. The advantage is that in problem-solving applications of the induced decision tree, the relevance of an attribute or test can be explained in terms of the strategy it was selected to support, such as confirming a target outcome class or eliminating a competing outcome class. However, it is possibl

RADE

D. J. Birnie,N. W. T. Harradine,D. Barnardsignificant effect on the performance of genetic search. In this paper, a statistics-based adaptive non-uniform mutation (SANUM) is presented within which the probability that each gene will subject to mutation is learnt adaptively over time and over the loci. As a search algorithm based on mechanis

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S. Shamiernational Conference on the theory, practice and application of Artificial Intelligence, held in Cambridge in December 2003. The conference was organised by SGAI, the British Computer Society Specialist Group on Artificial Intelligence (previously known as SGES). The papers in this volume present n