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Diffusion Evolutionary Algorithm
Mészáros, István ; Pospíchal, Petr (referee) ; Jaroš, Jiří (advisor)
There are new trends in artificial intelligence nowadays. Methods known as evolutionary algorithms are one of them. These algorithms allow us to design and optimize systems using computers. One of the variants of evolutionary algorithms is the diffusion evolutionary algorithm. This type of algorithms is able to run in parallel, and besides that it brings many positive features. The question is under what conditions the diffusion variant of evolutionary algorithms can effectively be used. Is it possible to use for planning systems and for problem optimization? Why are they more favorable than other types of evolutionary algorithms? This work tries to answer these questions and explain the behavior of these algorithms.
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Symbolic Regression and Coevolution
Drahošová, Michaela ; Žaloudek, Luděk (referee) ; Sekanina, Lukáš (advisor)
Symbolic regression is the problem of identifying the mathematic description of a hidden system from experimental data. Symbolic regression is closely related to general machine learning. This work deals with symbolic regression and its solution based on the principle of genetic programming and coevolution. Genetic programming is the evolution based machine learning method, which automaticaly generates whole programs in the given programming language. Coevolution of fitness predictors is the optimalization method of the fitness modelling that reduces the fitness evaluation cost and frequency, while maintainig evolutionary progress. This work deals with concept and implementation of the solution of symbolic regression using coevolution of fitness predictors, and its comparison to a solution without coevolution. Experiments were performed using cartesian genetic programming.
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Intelligent Web Work Planner
Kmeť, Miroslav ; Vrábel, Lukáš (referee) ; Čermák, Martin (advisor)
This thesis describes basic principles governing the use of evolutionary algorithms. Thesis deals with the usage of the evolutionary algorithms for scheduling the work between group of employees. Genetic algorithms, which represents intelligent stochastic optimization techniques based on the mechanism of natural selection and genetics are mainly used to solve this problem. Each solution is represented as an individual in population and only the most adapted ones are selected for the process of reproduction.
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Genetic Programming for Design of Digital Circuits
Hejtmánek, Michal ; Bidlo, Michal (referee) ; Gajda, Zbyšek (advisor)
The goal of this work was the study of evolutionary algorithms and utilization of them for digital circuit design. Especially, a genetic programming and its different manipulation with building blocks is mentioned in contrast to a genetic algorithm. On the basis of this approach, I created and tested a hybrid method of electronic circuit design. This method uses spread schemes according to the genetic algorithm for the pattern problems witch are solved by the genetic programming. The method is more successful and have faster convergence to a solution in difficult electronic circuits design than a common algorithm of the genetic programming.
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Boosting and Evolution
Mrnuštík, Michal ; Juránek, Roman (referee) ; Hradiš, Michal (advisor)
This thesis introduces combination of the AdaBoost and the evolutionary algorithm. The evolutionary algorithm is used to find linear combination of Haar features. This linear combination creates the feature to train weak classifier for AdaBoost. There are described basics of classification, Haar features and the AdaBoost. Next there are basic information about evolutionary algorithms. Theoretical description of combination of the AdaBoost and the evolutionary algorithm is included too. Some implementation details are added too. Implementation is tested on the images as part of the system for face recognition. Results are compared with Haar features.
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Comparison of Classification Methods
Dočekal, Martin ; Zendulka, Jaroslav (referee) ; Burgetová, Ivana (advisor)
This thesis deals with a comparison of classification methods. At first, these classification methods based on machine learning are described, then a classifier comparison system is designed and implemented. This thesis also describes some classification tasks and datasets on which the designed system will be tested. The evaluation of classification tasks is done according to standard metrics. In this thesis is presented design and implementation of a classifier that is based on the principle of evolutionary algorithms.
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Coevolutionary Algorithms Statistical Analysis Tool
Urban, Daniel ; Zachariášová, Marcela (referee) ; Drahošová, Michaela (advisor)
This bachelor thesis contains a theoretical basis that introduces evolutionary algorithms, genetic programming, coevolutioanary algorithms and methods for statistical evaluation. Furthermore, this work deals with the design and implementation of tool with graphical user interface, which allows the analysis of coevolutioanary algorithm for various parameters and also its statistical evaluation. The functionality of the implemented tool has been tested on data obtained from an external program performing evolutionary design of image filters with the use of the coevolution of tness predictors. The resulting graphs and statistics allow easy comparison of the progress and results for each program run.
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Evolution of CoreWar Warriors by Means of Genetic Algorithms
Tříska, Martin ; Beran, Vítězslav (referee) ; Zuzaňák, Jiří (advisor)
Evolutionary algorithms are a progressive and constantly evolving part of computer science. They are used mainly to solve the multidimensional problems with many local maxima, which are impossible to solve analytically. This thesis discusses how to use them for creating programs in Redcode language, which will be able to fight by the rules of game Corewars. Suggests possible representations of programs written in Redcode for evolutionary algorithms, discusses platform for evaluating their fitness and possible implementations of crossover and mutation. This thesis also contains application capable of development of such programs.
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