This paper investigates the issue of PID-controller parameter tuning for a magnetic levitation system using the nondominated sorting genetic algorithm (NSGA-II). The magnetic levi...
We present and evaluate a method for estimating the relevance and calibrating the values of parameters of an evolutionary algorithm. The method provides an information theoretic m...
Abstract. Isomap is a highly popular manifold learning and dimensionality reduction technique that effectively performs multidimensional scaling on estimates of geodesic distances....
We design algorithms for two online variance minimization problems. Specifically, in every trial t our algorithms get a covariance matrix Ct and try to select a parameter vector wt...
Testers often represent systems under test in input parameter models. These contain parameters with associated values. Combinations of parameter values, with one value for each pa...
The Terrain-Based Genetic Algorithm (TBGA) is a self-tuning version of the traditional Cellular Genetic Algorithm (CGA). In a TBGA, various combinations of parameter values appear...
V. Scott Gordon, Rebecca Pirie, Adam Wachter, Scot...
For types of data visualization where the cost of producing images is high, and the relationship between the rendering parameters and the image produced is less than obvious, a vi...
In this work, we explore the idea that parameter setting of stochastic metaheuristics should be considered as a multiobjective problem. The so-called “performance fronts” pres...
The performance of a Multiobjective Evolutionary Algorithm (MOEA) is crucially dependent on the parameter setting of the operators. The most desired control of such parameters pre...
Divide-and-Evolve (DaE) is an original “memeticization” of Evolutionary Computation and Artificial Intelligence Planning. However, like any Evolutionary Algorithm, DaE has se...