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C. FERREIRA In Leandro N. de Castro and Fernando J. Von Zuben, eds., Recent Developments in Biologically Inspired Computing, pages 82-103, Idea Group Publishing, 2004. Gene Expression Programming and the Evolution of Computer Programs Genetic Algorithms   Genetic algorithms were invented by John Holland in the 1960s and they also apply biological evolution theory to computer systems (Holland 1975). Like all evolutionary computer systems, GAs are an oversimplification of biological evolution. In this case, solutions to a problem are usually encoded in strings of 0’s and 1’s (chromosomes), and populations of such strings (individuals or candidate solutions) are used in order to evolve a good solution to a particular problem. From generation to generation candidate solutions are reproduced with modification and selected according to fitness. Modification in the original genetic algorithm was introduced by the genetic operators of mutation, crossover, and inversion. It is worth pointing out that GAs’ individuals consist of naked chromosomes or, in other words, GAs’ individuals are simple replicators. And like all simple replicators, the chromosomes of genetic algorithms function simultaneously as genotype and phenotype: they are both the object of selection and the guardians of the genetic information that must be replicated and passed on with modification to the next generation. Consequently, the whole structure of the replicator determines the functionality and, therefore, the fitness of the individual. For instance, in such systems it would not be possible to use only a particular region of the replicator as a solution to a problem: the whole replicator is always the solution: nothing more, nothing less. Home | Contents | Previous | Next