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Representation Techniques for Evolutionary Design of Cellular Automata
Kovács, Martin ; Drábek, Vladimír (referee) ; Bidlo, Michal (advisor)
The aim of this thesis is to experimentally evaluate the performance of several distinct representations of transition functions for cellular automata. Cellular automata have many potential applications for simulating various phenomena (e.g. natural processes, physical systems, etc.). Parallel computation of cellular automata is based on local cell interactions. Such computation, however, may prove difficult to program the CA, which is the reason for applying evolutionary techniques for the design of cellular automata in many cases. Evolutionary algorithms, based on Darwin's theory of evolution, have been used to find human-competitive solutions to many problems. In order to perform the evolutionary design of cellular automata, special encodings of the candidate solutions are often necessary. For this purpose the performance testing of various representations of the transition functions will be investigated. In particular, table representation, conditionally matching rules, and genetic programming will be treated. The problem of square calculations in cellular automata will be considered as a case study.
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Game in a Shader
Ivanecký, Ján ; Milet, Tomáš (referee) ; Polok, Lukáš (advisor)
This thesis deals with design and implementation of a simple strategic game using OpenGL, whose game logic is realized by the graphics card and rendering is realized by the graphics card in one shader. It also contains introduction to OpenGL, overview of techniques used for generating procedural textures and overview of rendering methods based on Ray Casting.
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Evolutionary Design of Moving Objects
Baláž, Martin ; Žaloudek, Luděk (referee) ; Bidlo, Michal (advisor)
This thesis deals with the utilization of evolutionary techniques to find such environment characteristics, that allow the object in this environment to perform the movement according to specified parameters. The environment which is utilized in this work is a cellular automaton, whose local transition function is optimized using the genetic algorithm. The principles of computational development are applied. The presented work tends to the area of theoretical biology. Its main objective is to create a simple simulator of life of artificial organisms. In particular, movement as a specific aspect of life is considered. For this purpose the application allows the designer to define an organism at the level of cells of the cellular automaton and apply the genetic algorithm to design the transition function specifying the behavior of the organism according to given parameters.
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Cellular Automata Simulation Library
Bocko, Dávid ; Křivánek, Jan (referee) ; Korček, Pavol (advisor)
This work describes concept and description of library for the cellular automata (CA) simulator. In the introduction is described brief history, types of CA and formal definition of CA. In the library implementation section is described the design of object-oriented model (classes, methods) and usage. Library of CA is created with regard to reusability, which allows to simply define any type of CA simulator. The Library was created in purpose to fill user's needs, because of lack of general CA simulator.
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Music Creation Using Cellular Automata
Novotný, Pavel ; Martinek, David (referee) ; Peringer, Petr (advisor)
In this thesis the cellular automata are used for algorithmic music composition. It contains a general overview of the algorithmic composition method and cellular automata. The crucial part of the thesis describes the concept and implementation of the program with a graphical user interface which uses two simple methods for conversion cellular automata's states into music. The final program was tested on several cellular automata and the sound outputs of both methods were compared with each other. The program is useful especially for the creation of short melodies.
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Evolutionary Design of Simulator Based on Cellular Automata
Brigant, Vladimír ; Šperka, Svatopluk (referee) ; Mrnuštík, Michal (advisor)
This work describes concept of a cellular automata (CA) simulator, which is able to predict behaviour of a complex spatial system. This prediction is based on available training data and transition rule acquired from regression analysis powered by evolutionary algorithms. Two regression analysis methods (linear and logistic regression) are suggested, implemented and compared on urban growth prediction of Brno city.
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GUI for Microscopic Traffic Simulation
Fülöp, Tibor ; Petrlík, Jiří (referee) ; Korček, Pavol (advisor)
Nowadays the road traffic is more complex and number of vehicles increases. The goal of this thesis is to develop microscopic traffic simulator with graphical user interface which it is possible to experiment with. The simulator can be used to construction of road topology with multiple lane roads and crossroads. It supports creating uncontrolled crossroads, crossroads with main road or crossroad with traffic lights. It generates and shows macroscopic data during simulation. It is based on cellular automaton and model is inspired by Nagel-Schreckenberg traffic model. There are results of simulating simple traffic simulations in the thesis.
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Intelligent Control of Traffic Lights
Skoták, Miloš ; Samek, Jan (referee) ; Malačka, Ondřej (advisor)
In this thesis is analyzed Multi-Agent system for intelligent control of traffic lights. For the simulation of a real situation was implemented a simulator of a traffic situation written in Java language, which is based on a cellular automata. In Multi-Agent system can be found not only communication between the agent and environment, but also communication among agents. To implement the rules was used extended AgentSpeak language model based on BSD with Jason interpreter. Experiments were done on a real road section in the city Brno.
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Prediction of the Secondary Structure of Proteins by Cellular Automaton
Šalanda, Vojtěch ; Vogel, Ivan (referee) ; Bendl, Jaroslav (advisor)
This thesis presents a new approach to the prediction of the secondary structure of proteins. It employs a new method based on cellular automata and its characteristic properties. The main objective is to increase speed of the prediction even at the cost of slight decrease of overall accuracy. Optimal parameters of cellular automata was found by genetic algorithm using suitable genetic operators. These parameters are incorporated into developed application for prediction. Finally, the results was compared with results of other tools for this purpose.
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