Abstract. Parallel genetic algorithms are usually implemented on parallel machines or distributed systems. This paper describes how finegrained parallel genetic algorithms can be ...
The coauthorship and coeditorship relations as recorded in the genetic programming bibliography provide a quantitative view of the GP community. Eigen analysis is used to find the ...
William B. Langdon, Riccardo Poli, Wolfgang Banzha...
Two prominent genetic programming approaches are the graph-based Cartesian Genetic Programming (CGP) and Linear Genetic Programming (LGP). Recently, a formal algorithm for construc...
Abstract. This paper proposes a decision support system for tactical air combat environment using a combination of unsupervised learning for clustering the data and an ensemble of ...
Using a strongly typed functional programming language for genetic programming has many advantages, but evolving functional programs with variables requires complex genetic operat...