Genetic programming (GP) is a special form of genetic algorithm – the technique we have been applying throughout this entire book. In this special case, the candidate solutions – or individuals – that we are evolving with the aim of finding the best one for our purpose are actual computer programs, hence the name. In other words, when we apply GP, we evolve computer programs with the goal of finding a program that will excel at performing a particular task.
As you may recall, genetic algorithms use a representation of the candidate solutions, often referred to as a chromosome. This representation is the subject of genetic operators, namely selection, crossover, and mutation. Applying these operators to the current generation results in a new generation of solutions that is expected to produce better results than its predecessor. In most...
