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C. FERREIRA Invited Tutorial Presented at WSC6, 2001 Gene Expression Programming in Problem Solving Genetic Operators and Evolution   Genetic operators are the core of all genetic algorithms, and two of them are common to all evolutionary systems: selection and replication. Although the center of the storm, these operators, by themselves, do nothing in terms of evolution. In fact, they can only cause genetic drift, making populations less and less diverse with time until all the individuals are exactly the same (see Figures 4 and 5 in the next section). So, the cornerstone of all evolutionary systems is modification, or more specifically, the genetic operators that cause variation. And different algorithms create this modification differently. For instance, GAs normally use mutation and recombination; GP uses almost exclusively GP-specific recombination; and GEP uses mutation, recombination and transposition. With the exception of GP, which is severely constrained in terms of tools of genetic modification, in GAs and GEP, it is possible to implement easily a vast set of genetic operators capable of causing genetic diversification (from now on, unless otherwise stated, I will use the designation ‘genetic operators’ to refer to those with intrinsic transforming power, putting selection and replication aside) because the chromosomes of both algorithms allow their easy implementation. In fact, I implemented several genetic operators in GEP in order to shed some light on the dynamics of evolutionary systems (Ferreira 2001), but what is important is to provide for the necessary degree of genetic diversification to allow evolution. Mutation alone (by far the most important operator) is capable of wonders. However, the interplay of mutation and the other genetic operators not only allows an effective evolution but also allows the duplication of building blocks, their circulation in the genetic pool, the creation of repetitive sequences, etc., making things really interesting. In the remainder of this section we will see how genetic operators (including selection and replication) work and how they can be easily implemented in GEP. Home | Contents | Previous | Next