What is genetic programming?
Genetic programming is the process of using one computer program to write another computer program using a methodology based on evolutionary algorithm. This process is often compared with linear programming, in which the programmer writes specific computer instructions to perform. Lisp and scheme are the most common programming languages for this type of work due to their functionality and high -level flexibility. As a result of its conceptual similarity to biological development, genetic programming is often cited as an example of computer technology inspired by bio. For example, GP could be used to create a program to draw a photo sketch. The first thing GP would do is to create a set of programs that use different features of computer drawing in random combinations. Then the GP would start each of these programs in order and released the results of everyone on the imagery.
the next step forGP is a selection of the best of these programs from the set. This process is generally the most difficult part of genetic programming. In the case of the drawing program, GP would use software to compare images to determine which of the random drawings was the most similar image that the software tried to draw. Of the randomly generated programs, the GP would choose the first few and throw away the rest. The selection process is known as fitness evaluation and is generally considered to be the most difficult part of genetic programming.
As soon as the best programs have been selected, GP will use them as the basis of a new dose of programs. Each new dose is called generation. Two ways of creating a new generation are mutations and crossover. The mutation works by taking one of the existing programs and making random changes, perhaps I will clean better. The crossover, also called breeding, works by taking two of the highest programs and combining their elements to create new programs.
After creating a new dose of GP programs repeats the process isStarting and evaluation and then repeats the processes of selection, elimination and generation. GPS will often run hundreds of generations before finding a single program with a satisfactory result. Despite this restriction, genetic programming is common to solve some types of difficult calculation problems, including problems with robotic engineering and artificial intelligence.