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Command Classification from EMG Using Neural Network
Zauška, Ján ; Šůstek, Martin (referee) ; Szőke, Igor (advisor)
This work deals with classification of 15 commands (short words), from small dataset recorded by sEMG electrodes placed on face and neck of speaker. Two types of speech are differentiated in recordings - audible speech, what is classic speech and silent speech, hence speech, in which sound output is suppressed. This work describes EMG signal processing, feature extraction, classifier design and classification results. The convolutional neural network architecture was used as a classifier. There are a lot of experiments in this work that compare the classification accuracy of silent and audible speech.
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Strategic Game in Multi-Agent System Jason
Leško, Matej ; Samek, Jan (referee) ; Král, Jiří (advisor)
Tato práce se zaobírá problematikou koncepce a vývoje multi-agentní tahové strategické hry. Práce analyzuje teorii těchto her a agentních systémů a výsledky této analýzy následně zohledňuje v návrhu samotné hry. Ta implementuje kromě herních konceptů a ovládání, obecně užívaných, dvě úrovně kooperace umělé inteligence, mírnou a komplexní spolupráci. Agent je v této hře hráčem, ovládajícím různé jednotky. Hra je koncipovaná tak, že je jí možné rozšířit o nové druhy inteligence, případně o nové herní jednotky. Závěrečná část práce se soustředí na srovnání jednotlivých úrovní kooperace, na efektivitu jednotlivých umělých inteligencí a také na zhodnocení efektivity implementace hry. S tímto účelem byla vykonána série automatizovaných testů.
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FPS
Konečný, Dominik ; Kudělka, Vladimír (referee) ; Vaněk, Vojtěch (advisor)
This text documents the creation of a prototype of core systems in a digital FPS (first person shooter) game. There are two goals. One is to fulfill all the requirements of the genre and to follow up on its history. The second one is to try and find new approaches to individual elements from the design perspective, but also their connections and controls. The elements themselves are movement (walking, running, jumping etc) and combat (shooting, aiming, enemies and their capabilities and intelligence). Also the work is about finding ways how to transmit information through immersive user interface, mainly virtual hands and items. Throughout the work I focus on the elements one at a time. First I shortly describe what they are and their purpuse, then a bit about their history and in the end I describe my approach.
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Reversi
Labaj, Tomáš ; Jurka, Pavel (referee) ; Rozman, Jaroslav (advisor)
In this bachelor thesis present the problematic of an Artificial Intelligence and its usage for the board game Reversi is described. The best solution for this type of application is "minimax" method. To avoid redundant seeking through status field it is better to use some kind of limitations, e. c. Alpha-Beta method. Both methods are also described in this thesis. Second part is focused on self- learning computer algorithms (the ways how computer can improve his turn after unsuccessful one).
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Reinforcement Learning for Bomberman Type Game
Adamčiak, Jakub ; Beran, Vítězslav (referee) ; Hradiš, Michal (advisor)
This bachelor's thesis aims to develop, implement and train reinforcement learning models for a Bomberman-type game. It is based on Bomberland environment from CoderOne. This environment was created for education and research in the field of artificial intelligence. In this thesis I tackle the settings and problems of implementing agent into the environment. I used 2 policies (MLP and CNN), 2 algorithms (PPO and A2C) and 5 setups of neural networks for feature extraction with the use of libraries stable baselines 3 and pytorch. Total training time resulted in 1207 real-world hours, 4168 computing hours and 271 milions of time steps. Although the training was not successful, this thesis shows the process of implementing a reinforcement learning model into a Gym environment.
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Distributed Artificial Life Simulator
Weiss, Martin ; Kočí, Radek (referee) ; Martinek, David (advisor)
Along with the artificial intelligence modelling and related studies, distributed computing ranks amongs the most discussed scientific topics nowadays and one can be certain that it will not fade away anytime soon. This work is also concerned about the above mentioned topics, more precisely its its main goal is to design and implement a distributed artificial intelligence simulator. The mentioned application was realized during as an firm part of this work and some benchmarks were run to determine and observe some properties inherent to distributed systems. The actual realization takes into account different approaches to distributing simulation resources. The final product did not prove as that convenient for simulation of rather simple AI models, which it if fact, even slowed down at times. In the future the project should be aimed towards more computationally challenging problems, that can truly use the capacity and advantages of such a computational system.
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Robotic Tracking of a Person using Neural Networks
Zakarovský, Matúš ; Lázna, Tomáš (referee) ; Žalud, Luděk (advisor)
Hlavným cieľom práce bolo vytvorenie softvérového riešenia založeného na neurónových sieťach, pomocou ktorého bolo možné detegovať človeka a následne ho nasledovať. Tento výsledok bol dosiahnutý splnením jednotlivých bodov zadania tejto práce. V prvej časti práce je popísaný použitý hardvér, softvérové knižnice a rozhrania pre programovanie aplikácií (API), ako aj robotická platforma dodaná skupinou robotiky a umelej inteligencie ústavu automatizácie a meracej techniky Vysokého Učenia Technického v Brne, na ktorej bol výsledný robot postavený. Následne bola spracovaná rešerš viacerých typov neurónových sietí na detekciu osôb. Podrobne boli popísané štyri detektory. Niektoré z nich boli neskôr testované na klasickom počítači alebo na počítači NVIDIA Jetson Nano. V ďalšom kroku bolo vytvorené softvérové riešenie tvorené piatimi programmi, pomocou ktorého bolo dosiahnuté ciele ako rozpoznanie osoby pomocou neurónovej siete ped-100, určenie reálnej vzdialenosti vzhľadom k robotu pomocou monokulárnej kamery a riadenie roboty k úspešnému dosiahnutiu cieľa. Výstupom tejto práce je robotická platforma umožnujúca detekciu a nasledovanie osoby využiteľné v praxi.
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Fast Adaptation of Codenames Computer Assistant for New Languages
Jareš, Petr ; Otrusina, Lubomír (referee) ; Smrž, Pavel (advisor)
This thesis extends a system of an artificial player of a word-association game Codenames to easy addition of support for new languages. The system is able to play Codenames in roles as a guessing player, a clue giver or, by their combination a Duet version player. For analysis of different languages a neural toolkit Stanza was used, which is language independent and enables automated processing of many languages. It was mainly about lemmatization and part of speech tagging for selection of clues in the game. For evaluation of word associations were several models tested, where the best results had a method Pointwise Mutual Information and predictive model fastText. The system supports playing Codenames in 36 languages comprising 8 different alphabets.
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Game in OpenGL
Hranáč, Pavel ; Milet, Tomáš (referee) ; Starka, Tomáš (advisor)
The goal of this thesis is to create a custom game with an AI opponent. The theoretical part of the thesis deals mainly with artificial intelligence in games in general. The game's graphics are three-dimensional and use the OpenGL API and the GPUEngine graphics library. The created game is a turn-based strategy game similar to chess, offering computer opponents of various difficulties using a custom modification of the Minimax strategy with a complex heuristic. The game also offers local multiplayer. The results of this thesis can serve as inspiration or a basis for the study of artificial intelligence in games.
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