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C. FERREIRA Invited Tutorial Presented at WSC6, 2001 Gene Expression Programming in Problem Solving Genetic Algorithms at Large   The aim of this introduction is to bring into focus the basic differences between gene expression programming (GEP) and its predecessors, genetic algorithms (GAs) and genetic programming (GP). According to Mitchell (1996), gene expression programming is, like GAs and GP, a genetic algorithm as it uses populations of individuals, selects them according to fitness, and introduces genetic variation using one or more genetic operators. The fundamental difference between the three algorithms resides in the nature of the individuals: in GAs the individuals are symbolic strings of fixed length (chromosomes); in GP the individuals are non-linear entities of different sizes and shapes (parse trees); and in GEP the individuals are encoded as symbolic strings of fixed length (chromosomes) which are then expressed as non-linear entities of different sizes and shapes (expression trees). Home | Contents | Previous | Next