Abstract. The problem of parallel and distributed function optimization with coevolutionary algorithms is considered. Two coevolutionary algorithms are used for this purpose and co...
Franciszek Seredynski, Albert Y. Zomaya, Pascal Bo...
This paper introduces Dafo, a new multi-agent framework for evolutionary optimization relying on a competitive coevolutionary genetic algorithm, aka LCGA (Loosely Coupled Genetic A...
In this paper we demonstrate how genetic algorithms can be used to reverse engineer an evaluation function’s parameters for computer chess. Our results show that using an appropr...
Omid David-Tabibi, Moshe Koppel, Nathan S. Netanya...
Optimization of the control parameters of genetic algorithms is often a time consuming and tedious task. In this work we take the meta-level genetic algorithm approach to control ...