Convergence (evolutionary computing)
Encyclopedia
Precisely every individual in the population is identical. While full convergence might be seen in genetic algorithms using only cross over
, such convergence is seldom seen in genetic programming
using Koza's subtree swapping crossover. However, populations often stabilise after a time, in the sense that the best programs all have a common ancestor and their behaviour is very similar (or identical) both to each other and to that of high fitness programs from the previous (and future?) generations. Often the term convergence is loosely used.
Crossover (genetic algorithm)
In genetic algorithms, crossover is a genetic operator used to vary the programming of a chromosome or chromosomes from one generation to the next. It is analogous to reproduction and biological crossover, upon which genetic algorithms are based...
, such convergence is seldom seen in genetic programming
Genetic programming
In artificial intelligence, genetic programming is an evolutionary algorithm-based methodology inspired by biological evolution to find computer programs that perform a user-defined task. It is a specialization of genetic algorithms where each individual is a computer program...
using Koza's subtree swapping crossover. However, populations often stabilise after a time, in the sense that the best programs all have a common ancestor and their behaviour is very similar (or identical) both to each other and to that of high fitness programs from the previous (and future?) generations. Often the term convergence is loosely used.