Advances in Evolutionary Computing: Theory and Applications by Ashish Ghosh, Shigeyoshi Tsutsui

By Ashish Ghosh, Shigeyoshi Tsutsui

This publication offers a set of fourty articles containing new fabric on either theoretical elements of Evolutionary Computing (EC), and demonstrating the usefulness/success of it for varied varieties of large-scale actual global difficulties. round 23 articles care for a variety of theoretical facets of EC and 17 articles exhibit the good fortune of EC methodologies. those articles are written by way of top specialists of the sphere from various nations around the globe.

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Extra info for Advances in Evolutionary Computing: Theory and Applications (Natural Computing Series)

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4 , 335-360 50. K. C. (1999) Digital circ uit evolution and fitness landscap es . , IEEE Press, Piscataway, NY , 1299-1 306 51. K. C . (1999) On the nature of two-bit multiplier landscapes. : Proceedings of t he 1st NASA /DoD Workshop on Evolvable Hardwar e, Los Alamitos , CA , IEEE Computer Society, 36-45 52. K. C. (1999) Digital circuit evolut ion: The ruggedness and neu trality of two-bit multiplier landscap es. : Evolutionar y Hardwar e Systems, lEE P ress , London , 6/1-6/4 53. K . (2000) Principles in t he evolut ionary design of digital cir cui ts - part II .

For convenience, the fitn ess values are scaled in the int erval [0,1]. To enco de a digital elect ronic circ uit into a genotype, a genoty pe / phenotype mapping is defined . This is a rect an gular arr ay of cells each of which is an atomic two-input logic gate or a multiplexer. Thus t he genotyp e is a linea r string of int egers and it consist s of two different typ es of genes that are responsible for the funct ionality and the routing of the evolved array. It is important t o note t hat t he representation is restricted to allow only feedforw ard circuits since only combina t ional design is considered .

The figures represent the distribution of the amplitude spectra by classes (Figures 9a,11a and 13a-15a) and the estimated amplitude spectra versus the interaction order (Figures 9bd, 10b-d, 11band 13b-15b). The spectra of each class are represented by the class representative vector that is the average over the elements of the class. Standard deviations were also calculated and were found to be in the range from a to 10- 3 . The amplitude spectra of the mutation landscapes reveal that only the first 7, 12 and 2 amplitudes may respectively contribute to the ruggedness of functionality, internal connectivity and output connectivity landscapes.

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