Download e-book for iPad: Advances in Case-Based Reasoning: Second European Workshop, by Eva Armengol, Enric Plaza (auth.), Jean-Paul Haton, Mark

By Eva Armengol, Enric Plaza (auth.), Jean-Paul Haton, Mark Keane, Michel Manago (eds.)

This booklet offers a variety of revised refereed papers taken from the contributions to the second one eu Workshop on Case-Based Reasoning, EWCBR-94, held on the Abbaye de Royaumont close to Paris in November 1994. The 22 papers integrated have been selected from a complete of 60 submissions. the $64000 evolution via skilled synthetic intelligence over the past few years has been primarily stimulated via case-based reasoning, fairly by way of the realm of knowledge-based determination help. This publication records the development completed in CBR equipment and instruments throughout the very contemporary earlier. It additionally outlines the tremendous luck completed within the functions area, specially within the fields of structure and computer-aided layout, job making plans, chemical synthesis, upkeep and analysis, and law.

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Read Online or Download Advances in Case-Based Reasoning: Second European Workshop, EWCBR-94 Chantilly, France, November 7–10, 1994 Selected Papers PDF

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A simulated annealing like convergence theory for the simple genetic algorithm. In: (Belew and Booker, 1991), 174-181 7. A. and J. : Pattern Recognition: A statistical Approach. Prentice-Hall International. Hemel Hemstead, Hertfordshire, UK (1982) 8. Goldberg, D. : Genetic Algorithms: Search, Optimization and Machine Learning. Addison-Wesley, Reading, MA (1989) 9. K. C. : Algorithms for Clustering Data. Prentice-Hall, Englewood Cliffs, NJ (1988) 10. D. Chaudhuri, C. A. Murthy and B. B. ” IEEE SMC, 24(9) (1994) 1416- 1424 11.

The remaining part of this section describes in detail the genetic algorithm that we propose for clustering. First, the string representation and the initial population for the problem under consideration are discussed. Then the genetic operators and the way they are used are stated. The last part of this section deals with the stopping criteria for the GA. 1 String Representation and Initial Population String representation: To solve partitioning problems with GAs, one must encode partitions in a way that allows manipulation by genetic operators.

E. J. : A simulated annealing like convergence theory for the simple genetic algorithm. In: (Belew and Booker, 1991), 174-181 7. A. and J. : Pattern Recognition: A statistical Approach. Prentice-Hall International. Hemel Hemstead, Hertfordshire, UK (1982) 8. Goldberg, D. : Genetic Algorithms: Search, Optimization and Machine Learning. Addison-Wesley, Reading, MA (1989) 9. K. C. : Algorithms for Clustering Data. Prentice-Hall, Englewood Cliffs, NJ (1988) 10. D. Chaudhuri, C. A. Murthy and B. B. ” IEEE SMC, 24(9) (1994) 1416- 1424 11.

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