Genetic programming starts with a primordial ooze of thousands of randomly created computer programs. This population of programs is progressively evolved over a series of generations. The evolutionary search uses the Darwinian principle of natural selection (survival of the fittest) and analogs of various naturally occurring operations, including crossover (sexual recombination), mutation, gene duplication, gene deletion. Genetic programming sometimes also employs developmental processes by which an embryo grows into fully developed organism. Old Chinese saying says “animated gif is worth one mega-word,” so click here for short tutorial of “What is GP?” including about two dozen animated gifs. This short tutorial contains a discussion of the preparatory steps of a run of genetic programming, the executional steps (that is, the flowchart of genetic programming), an illustrative simple run of genetic programming for a problem of symbolic regression of a quadratic polynomial, a discussion of developmental genetic programming for the automatic synthesis of both the topology and sizing of analog electrical circuits (potentially also including placement and routing), and the use of a turtle to draw complex structures (such as antenna). In addition, genetic programming can automatically create, in a single run, a general (parameterized) solution to a problem in the form of a graphical structure whose nodes or edges represent components and where the parameter values of the components are specified by mathematical expressions containing free variables. That is, genetic programming can automatically create a general solution to a problem in the form of a parameterized topology. 数据挖掘论坛
