The GP.Lab Genetic Programming Kernel (continued)
This second post on our custom Genetic Programming implementation covers selection and genetic operators implemented by the kernel. Selection Strategies The GP kernel implements a generational algorithm and currently supports the three most popular selection modes for choosing parents to produce offspring for the next generation: Tournament Selection , i.e. for a tournament size T randomly pick T programs from the parent population and return the winner of the tournament - the program with the best fitness. The selection method of choice in the GA community as it allows to fine-tune the selection pressure via the tournament size parameter to avoid premature loss of diversity (i.e. fittest programs dominating the population with their copies). Roulette Wheel , a flavor of Fitness Proportionate Selection where the chance of an individual to become a parent is proportional to its fitness, i.e. parents with the highest absolute fitness in the population have a higher chance o