Correlation Clustering was defined by Bansal, Blum, and Chawla as the problem of clustering a set of elements based on a possibly inconsistent binary similarity function between e...
The paper presents the parameter-less implementation of an evolutionary-based search. It does not need any predefined control parameters values, which are usually used for geneti...
Abstract- An evolutionary algorithm for the optimization of a function with real parameters is described in this paper. It uses a cooperative co-evolution to breed and reproduce su...
Abstract. Designing an adequate fitness function requiressubstantial knowledge of a problem and of features that indicate progress towards a solution. Coevolution takes the human ...
In this paper, we show how adaptive prototype optimization can be used to improve the performance of function approximation based on Kanerva Coding when solving largescale instanc...