Eight Queens with Evolutionary Computing

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Therefore in certain sense each species is a solution to fix a certain group of environmental challenges. Initialise Termination parent selection Population survivor selection Figure 1: Evolution flow diagram 3 <strong>Evolutionary</strong> Algorithms Parents Offspring recombination mutation <strong>Evolutionary</strong> algorithms follow the model given in Figure 1. The aspects of evolutionary algorithms are: • Representation (definition of individuals) • Fitness function (evaluation function) • Population (unit of evolution) • Parent selection (pushes quality) • Variation operators (recombination and mutation) • Survival selection (replacement) 2
Parent selection and survivor selection are selection operators which operate at population level whereas recombination and mutation are variation operators, and they operate on individuals. 3.1 Representation Representation defines the mapping between the genotype space and the phenotype space (see Figure 2). The entire genotype space of a species is called a genome. 3.2 Fitness function Figure 2: Evolution flow diagram Fitness function is a function or procedure that assigns a quality measure to genotypes. Essentially fitness function defines what improvement means. Fitness function needs to be applied upon the population during parent selection and survivor selection in order to determine the top (best) and the bottom (worst) end of a population [1]. 3
Page 1: Eight Queens with Evolutionary Comp
Page 5 and 6: 3.7 The Algorithm The pseudo code o
Page 7 and 8: where s is the interpolated fitness
Page 9 and 10: 5 Use Cases 5.1 Adaptation Rate Evo
Page 11 and 12: Mutation Probability Data Series Pr
Page 13 and 14: evocom started. ===================

Eight Queens with Evolutionary Computing

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