Learning genetic representation has been shown to be a useful tool in evolutionary computation. It can reduce the time required to find solutions and it allows the search process ...
This paper presents a modularization strategy for linear genetic programming (GP) based on a substring compression/substitution scheme. The purpose of this substitution scheme is t...
We introduce and apply a genetic representation for analog electronic circuits based on the association of character strings extracted from the genome with the terminals and param...
— An evolutionary algorithm automatically discovers suitable solutions to a problem, which may lie anywhere in a large search space of candidate solutions. In the case of Genetic...
A novel Grammatical Genetic Algorithm, the meta-Grammar Genetic Algorithm (mGGA) is presented. The mGGA borrows a grammatical representation and the ideas of modularity and reuse f...