The research reported in this paper is concerned with assessing the usefulness of reinforcment learning (RL) for on-line calibration of parameters in evolutionary algorithms (EA). ...
A. E. Eiben, Mark Horvath, Wojtek Kowalczyk, Marti...
Simulation of natural human movement has proven to be a challenging problem, difficult to be solved by more or less traditional bioinspired strategies. In opposition to several exi...
Y. Bellan, Mario Costa, Giancarlo Ferrigno, Fabriz...
In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...
Robotic controllers take advantage from neural network learning capabilities as long as the dimensionality of the problem is kept moderate. This paper explores the possibilities of...
This paper proposes a multilevel logic approach to output coding using multilevel neurons in the output layer. Training convergence for a single multilevel perceptron is considere...
Aleksander Malinowski, Tomasz J. Cholewo, Jacek M....