Oleg Kovářík

My photographOleg Kovářík joined the group in 2007 as a Ph.D. student. His research is focused on Ant Colony Optimization and realted swarm algorithms, their parallelization and applications in datamining.



  • Oleg Kovářík, Richard Málek: Meta-learning and meta-optimization. , 2012 BibTex, PDF
  • Pavel Kordík, Oleg Kovářík, Miroslav Šnorek: Optimization of Models: Looking for the Best Strategy. In: Proceedings of 6th EUROSIM Congress on Modelling and Simulation, , Ljubjana, 2007. ISBN 3-901608-32-X BibTex, PDF

    When parameters of model are being adjusted, model is learning to mimic the behaviour of a real world system. Optimization methods are responsible for parameters adjustment. The problem is that each real world system is different and its model should be of different complexity. It is almost impossible to decide which optimization method will perform the best (optimally adjust parameters of the model). In this paper we compare the performance of several methods for nonlinear parameters optimization. The gradient based methods such as Quasi-Newton or Conjugate Gradient are compared to several nature inspired methods. We designed an evolutionary algorithm selecting the best optimization methods for models of various complexity. Our experiments proved that the evolution of optimization methods for particular problems is very promising approach.