Genetic algorithms

Abstract

Anthony Pioli April 4, 1997 When we hear the terms \genetic" and \algorithm", we normally would not concatenate the two together. This paper describes \genetic algorithms" and hopefully shows that the two terms can be used together. In the rst part, I explain what genetic algorithms are and how they work. In the second section, some examples are shown, and nally some concluding remarks are made. 1 What is a Genetic Algorithm? A genetic algorithm is a search algorithm. It 'evolves' a set of possible solutions until a satisfactory one is found. The basic idea is that a particular solution will pass its informational content onto its successors if it is a 'good' solution. The better the solution is, the higher is the probability of passing on its information; survival of the ttest in other words. In Fig. 1 I have shown a simple function, f(x). This particular function has a domain of all integers from 0 to 255 and a range of [0.0,1.0]. 1.0