Evolutionary computation methods have been used to solve several optimization and learning problems. This paper describes an application of evolutionary computation methods to con...
In this paper we examine how the choice of functions in a genetic program (GP) affects the rate of code growth and the development of resilient individuals. We find that functio...
Abstract. In this paper we continue our study on adaptive genetic programming. We use Stepwise Adaptation of Weights (saw) to boost performance of a genetic programming algorithm o...
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...
This contribution proposes an enhanced and generic selection model for Genetic Algorithms (GAs) and Genetic Programming (GP) which is able to preserve the alleles which are part o...
Michael Affenzeller, Stefan Wagner 0002, Stephan M...