P O Z V Á N K A
Dňa 27. júna 2006 o 14:00 bude v zasadacej miestnosti ústavov FIIT (Ilkovičova 3, blok D, 1. poschodie, miestnosť D 124) prednáška
Probabilistic Model-Building Genetic Algorithms
Martin Pelikán
Department of Mathematics and Computer Science
University of Missouri at St. Louis
St. Louis, Missouri, USA
Abstract
Probabilistic model-building algorithms (PMBGAs) replace traditional variation of genetic and evolutionary algorithms by (1) building a probabilistic model of promising solutions and (2) sampling the built model to generate new candidate solutions. Replacing traditional crossover and mutation operators by building and sampling a probabilistic model of promising solutions enables the use of machine learning techniques for automatic discovery of problem regularities and exploitation of these regularities for effective exploration of the search space. Using machine learning in optimization enables the design of optimization techniques that can automatically adapt to the given problem. This talk provides a gentle introduction to PMBGAs with an overview of major research directions in this area. Strengths and weaknesses of different PMBGAs will be discussed and suggestions will be provided to help practitioners to choose the best PMBGA for their problem.