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C. FERREIRA |
In A. Abraham, J. Ruiz-del-Solar, and M. Köppen (eds), Soft Computing Systems: Design, Management and Applications, pp. 153-162, IOS Press, Netherlands, 2002.
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Analyzing the Founder Effect in Simulated Evolutionary Processes Using Gene Expression Programming
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Genetic Algorithms |
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All genetic algorithms use populations of individuals, select individuals according to fitness, and introduce genetic variation using one or more genetic operators. Structurally, genetic algorithms can be subdivided in three fundamental groups: (1) Genetic algorithms with individuals consisting of linear chromosomes of fixed length devoid of complex expression. In these systems, replicators (chromosomes) survive by virtue of their own properties. The algorithm invented by Holland
[8] belongs to this group, and is known as genetic algorithm or GA; (2) Genetic algorithms with individuals consisting of ramified structures of different sizes and shapes and, therefore, capable of assuming a richer number of functionalities. In these systems, replicators (ramified structures) also survive by virtue of their own properties. The algorithm invented by Cramer
[2] and later developed by Koza [9] belongs to this group and is known as genetic programming or GP; and (3) Genetic algorithms with individuals encoded as linear chromosomes of fixed length which are afterwards expressed as ramified structures of different sizes and shapes. In these systems, replicators (chromosomes) survive by virtue of causal effects on the phenotype (ramified structures). The algorithm invented by myself
[4] belongs to this group and is known as gene expression programming or
GEP.
It is worth emphasizing that GEP shares with GP the same kind of ramified structure, meaning that both systems can be used in the same problem domains. However, due to the crossing of the phenotype threshold
[3], gene expression programming is bound to be much more successful, allowing the exploration of new frontiers in evolutionary computation. Below are briefly highlighted some of the differences between GP and GEP.
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