The No-Free-Lunch theorem is a fundamental result in the field of black-box function optimization. Recent work has shown that coevolution can exhibit free lunches. The question a...
A major difficulty for anomaly detection lies in discovering boundaries between normal and anomalous behavior, due to the deficiency of abnormal samples in the training phase. In...
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...
Though recent analysis of traditional cooperative coevolutionary algorithms (CCEAs) casts doubt on their suitability for static optimization tasks, our experience is that the algo...
Assume a coevolutionary algorithm capable of storing and utilizing all phenotypes discovered during its operation, for as long as it operates on a problem; that is, assume an algo...
This paper introduces the Objective Fitness Correlation, a new tool to analyze the evaluation accuracy of coevolutionary algorithms. Accurate evaluation is an essential ingredient...