National Repository of Grey Literature 13 records found  1 - 10next  jump to record: Search took 0.00 seconds. 
Evolutionary Analogue Amplifier Optimisation
Bielik, Marek ; Zachariášová, Marcela (referee) ; Bidlo, Michal (advisor)
Táto práca demonštruje možnosti využitia evolučných algoritmov, konkrétne evolučných stratégií, v doméne dizajnu analógových zosilňovačov. Do implementácie je zahrnutý ngSPICE simulátor, ktorý je použitý na vyhodnotenie optimalizovaných riešení a v práci je navrhnutých niekoľko vyhodnocovacích metód. Práca tiež zahŕňa experimenty a ich výsledky, ktoré boli použité na určenie najvodnejších parametrov evolučných stratégií. Cieľom bolo optimalizovať hodnoty súčiastok jedno a dvoj stupňových zosilňovačov s bipolárnymi tranzistormi v zapojení so spoločným emitorom. Výsledkom je nástroj umožňujúci návrh zosilňovačov s ľubovoľným zosilnením v rámci možností daného obvodu bez použitia akéhokoľvek matematického aparátu.
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.
Software for Biometric Recognition of a Human Eye Iris
Maruniak, Lukáš ; Orság, Filip (referee) ; Drahanský, Martin (advisor)
In my thesis, I focus on the task of recognizing human iris from an image.In the beginning, the work deals with a question of biometrics, its importance and basic concepts, which are necessary for use in following text. Subsequently process of human Iris detection is described together with theory of evolution algorithms. In the implementation part, is described the design of implemented solution, which uses evolution algorithms, where is emphasis on correct pupil and iris boundary detection.
Deep Learning AI in Game Environments
Glós, Kristián ; Bobák, Petr (referee) ; Polášek, Tomáš (advisor)
This thesis is focused on analysing deep learning algorithms and their ability to complete given tasks implemented in game environments created via the Unity game engine. Secondary objective was to research and specify possible use-cases of deep learning during game development. The algorithms used fall into Reinforcement learning, Imitation learning and Neuroevolution, while Reinforcement learning was used throughout the whole game scene development cycle. Analysis and results were collected through training the networks in different game scene states and other factors.
Evolutionary Algorithms
Szöllösi, Tomáš ; Mézl, Martin (referee) ; Kozumplík, Jiří (advisor)
The task of this thesis was focused on comparison selected evolutionary algorithms for their success and computing needs. The paper discussed the basic principles and concepts of evolutionary algorithms used for optimization problems. Author programmed selected evolutionary algorithms and subsequently tasted on various test functions with exactly the given input conditions. Finally the algorithms were compared and evaluated the results obtained for different settings.
Deep Learning AI in Game Environments
Glós, Kristián ; Bobák, Petr (referee) ; Polášek, Tomáš (advisor)
This thesis is focused on analysing deep learning algorithms and their ability to complete given tasks implemented in game environments created via the Unity game engine. Secondary objective was to research and specify possible use-cases of deep learning during game development. The algorithms used fall into Reinforcement learning, Imitation learning and Neuroevolution, while Reinforcement learning was used throughout the whole game scene development cycle. Analysis and results were collected through training the networks in different game scene states and other factors.
Evolutionary Algorithms for the Control of Heterogeneous Robotic Swarms
Karella, Tomáš ; Pilát, Martin (advisor) ; Balcar, Štěpán (referee)
Robotic swarms are often used for solving different tasks. Many articles are focused on generating robot controllers for swarm behaviour using evolutionary algorithms. Most of them are nevertheless considering only homogenous robots. The goal of this thesis is to use evolutionary algorithms for behaviours of heterogeneous robotic swarms. A 2D simulation was implemented to explore swarm controller optimization methods with the ability to create custom scenarios for robotic swarms. We tested differential evolution and evolution strategies on three different scenarios.
Evolutionary Analogue Amplifier Optimisation
Bielik, Marek ; Zachariášová, Marcela (referee) ; Bidlo, Michal (advisor)
Táto práca demonštruje možnosti využitia evolučných algoritmov, konkrétne evolučných stratégií, v doméne dizajnu analógových zosilňovačov. Do implementácie je zahrnutý ngSPICE simulátor, ktorý je použitý na vyhodnotenie optimalizovaných riešení a v práci je navrhnutých niekoľko vyhodnocovacích metód. Práca tiež zahŕňa experimenty a ich výsledky, ktoré boli použité na určenie najvodnejších parametrov evolučných stratégií. Cieľom bolo optimalizovať hodnoty súčiastok jedno a dvoj stupňových zosilňovačov s bipolárnymi tranzistormi v zapojení so spoločným emitorom. Výsledkom je nástroj umožňujúci návrh zosilňovačov s ľubovoľným zosilnením v rámci možností daného obvodu bez použitia akéhokoľvek matematického aparátu.
Evolutionary algorithms and active learning
Repický, Jakub ; Holeňa, Martin (advisor) ; Fink, Jiří (referee)
Názov práce: Evoluční algoritmy a aktivní učení Autor: Jakub Repický Katedra: Katedra teoretické informatiky a matematické logiky Vedúci diplomovej práce: doc. RNDr. Ing. Martin Holeňa, CSc., Ústav informa- tiky, Akademie věd České republiky Abstrakt: Vyhodnotenie ciel'ovej funkcie v úlohách spojitej optimalizácie často do- minuje výpočtovej náročnosti algoritmu. Platí to najmä v prípade black-box fun- kcií, t. j. funkcií, ktorých analytický popis nie je známy a ktoré sú vyhodnocované empiricky. Témou urýchl'ovania black-box optimalizácie s pomocou náhradných modelov ciel'ovej funkcie sa zaoberá vel'a autorov a autoriek. Ciel'om tejto dip- lomovej práce je vyhodnotit' niekol'ko metód, ktoré prepájajú náhradné modely založené na Gaussovských procesoch (GP) s Evolučnou stratégiou adaptácie ko- variančnej matice (CMA-ES). Gaussovské procesy umožňujú aktívne učenie, pri ktorom sú body pre vyhodnotenie vyberané s ciel'om zlepšit' presnost' modelu. Tradičné náhradné modely založené na GP zah'rňajú Metamodelom asistovanú evolučnú stratégiu (MA-ES) a Optimalizačnú procedúru pomocou Gaussovských procesov (GPOP). Pre účely tejto práce boli oba prístupy znovu implementované a po prvý krát vyhodnotené na frameworku Black-Box...
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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