The Evolutionary Requirements Analyser (ERA) applies evolutionary computing techniques to automatically select optimal combinations of human and machine agents in a system model to match nonfunctional requirements (NFRs). The tool assesses the reliability, performance times and cost of different system models by executing many model variants, as evolving forms, with scenarios and different comb...

This study evolves and categorises a population of conceptual designs by their ability to handle physical constraints. The design process involves a trade-off between form and function. The aesthetic considerations of the designer are constrained by physical considerations and material cost. In previous work, we developed a design grammar capable of evolving aesthetically pleasing designs throu...

This paper discusses the subject of automatic evolutionary sound matching: systems in which evolutionary algorithms are used to automatically derive the parameters of a synthesiser to produce a sound that matches a specified target sound. The paper describes prior work and identifies the principal causes of match inaccuracy, which are often due to optimiser limitations as a result of search spa...

The determination of the number of groups in a dataset, their composition and the most relevant measurements to be considered in clustering the data, is a high-demanding task, especially when the a priori information on the dataset is limited. Some different genetic approaches are proposed as tools for automatic data clustering and features selection. They differ in the adopted codification of ...

A methodology of comparative analysis of evolutionary models is proposed. The main aim of this proposition is to identify to what extend different models can be called ‘evolutionary ones’. Each model is analysed by searching for answers to following questions: • Is the model dynamical one? • Is it focused on far-from-equilibrium analysis? • What are a unit of evolution and a unit of selection? ...

We consider the problem of selecting investment components according to two partially opposed measures: the portfolio performance and its risk. We approach this within Markowitz’s model, considering the case of mutual funds market in Europe until July 2010. Comparisons were made on three multi-objective evolutionary algorithms, namely NSGAII, SPEA2 and IBEA. Two well-known performance measures ...

In this paper, an evolutionary programming-based clustering algorithm is proposed. The algorithm effectively groups a given set of data into an optimum number of clusters. The proposed method is applicable for clustering tasks where clusters are crisp mad spherical. This algorithm determines the number of clusters and the cluster centers in such a way that locally optimal solutions are avoided....

We prove that any deterministic evolutionary dynamic satisfying four mild requirements does not eliminate strictly dominated strategies in some games. We also show that existing elimination results for evolutionary dynamics are not robust to small changes in the specifications of the dynamics. Numerical analysis reveals that dominated strategies can persist at nontrivial frequencies even when t...

The EvoMove system is a motion-based musical companion that relies on a commensal computing scheme. The system relies on wireless sensors to detect dancer moves. The sensor information is sent to KymeroClust, an evolutionary algorithm that identifies and maintains a clustering model of the move categories. The system uses this information to play audio samples according to the detected categori...