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Expert system for diagnosis of diabetes
Braniš, Lukáš ; Jurajda, Michal (referee) ; Jirsík, Václav (advisor)
This thesis deals with the design and creation of a knowledge base for the NPS diagnostic expert system. The knowledge base is designed to diagnose diabetes and its specific type. Part of the thesis is a brief introduction to the issue of artificial intelligence, acquaintance of the reader with the theory of expert systems and knowledge engineering. Further, the thesis deals with the complex issue of the disease diabetes mellitus, its types, properties, symptoms and diagnosis.
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Methods for Playing the Game 'Liar's Dice' Using Dynamic Programming
Lohn, Marek ; Šátek, Václav (referee) ; Zbořil, František (advisor)
This project is about Methods of playing game Liar’s Dice using dynamic programming. The algorithm that was chosen for my study is SARSA, short for State Action Reward State Action algorithm. It is a modified version of algorithm named Q-Learning. It comparing algorithm SARSA with other algorithms by letting them play against each other in application, that was made in Unity Engine. Algorithms that were compared to SARSA are Q-Learning and Counterfactual Regret Minimization. SARSA achieved a 69,147 % win ratio in a game against Q-Learning. In games against Counterfactual Regret Minimization it was only 25 % win ratio. The main outcome of this study is that modified SARSA is effective against Q-Learning algorithm in a game of Liar’s Dice. On the other hand the SARSA algorithm was very ineffective against the Counterfactual Regret Minimization algorithm.
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Survival/Exploration Game in Unity
Klaban, Tomáš ; Matýšek, Michal (referee) ; Vlnas, Michal (advisor)
This bachelor's thesis is focused on the development of a survival game in the game engine Unity. The game is implemented in the top-down perspective and contains survival game mechanics in the form of enemy combat, environment exploration and improving character's attributes. The game world is fully procedurally generated in chunks using Perlin noise and Poisson disk sampling algorithm. The thesis explores various ways of procedural generation, which include noise, cellular automata and genetic algorithms. The thesis also contains theoretical knowledge about pseudorandom generators, artificial intelligence and pathfinding algorithms.
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Self-Modifying Cellular Automata
Szabo, Peter ; Drábek, Vladimír (referee) ; Bidlo, Michal (advisor)
This work deals with cellular automata with a concept of self- modification and their comparsion against regular cellular automatons . For this task we constructed a simulator , that lets us define the logic of artificial inteligence, number generator and statistical test, which are used by the automata , on their own . Consequently two experiments are carried out that demonstrate the concept of self- modification .
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The Use of Means of Artificial Intelligence for the Decision Making Support on Stock Market
Vaško, Jan ; Kříž, Jiří (referee) ; Dostál, Petr (advisor)
Diploma thesis deals with analyzing the possibility of using artificial intelligence, specifically artificial neural networks and fuzzy logic, on the capital markets as a tool to support decision making in business. The Matlab software is used for this purpose. The work is divided into three parts. The first part deals with theoretical knowledge, brief description of the current situationin is covered in a second part and the theoretical solutions are applied to the system in the third section.
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Methods of deep learning in image processing tasks
Polášková, Lenka ; Marcoň, Petr (referee) ; Mikulka, Jan (advisor)
The clue of learning to recognize objects using neural network lies in imitation of animal neural network's behavior. In spite the details of how brain works is not known yet, the teams consisting of scientists from various medical or technical professions are trying to search for them. Thanks to giants like Geoffrey Hinton science made a big progress in this domain. The convolutional networks which are based on animal model of optical system can be advantageously used for image segmentation and therefore they ware chosen for segmentation of tumor and edema from images of magnetic resonance. The models of artificial neural networks used in this work had achieved the 41\% of success in edema segmentation and 79\% in segmentation of tumor from brain issue.
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Word2vec Models with Added Context Information
Šůstek, Martin ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
This thesis is concerned with the explanation of the word2vec models. Even though word2vec was introduced recently (2013), many researchers have already tried to extend, understand or at least use the model because it provides surprisingly rich semantic information. This information is encoded in N-dim vector representation and can be recall by performing some operations over the algebra. As an addition, I suggest a model modifications in order to obtain different word representation. To achieve that, I use public picture datasets. This thesis also includes parts dedicated to word2vec extension based on convolution neural network.
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Creating a knowledge base for the diagnosing of diseases
Macháček, Daniel ; Steinerová, Kateřina (referee) ; Jirsík, Václav (advisor)
This bachelor thesis is focused on problematic of creation knowledge base. It is describing basics of expert systems, their function and possible usage in modern world. In result of this thesis is knowlenge base in web aplication NPS able to diagnose diseases of hematology-oncology and that is proving possibility for use in real life. Knowledge base was created in cooperation with experts in the medical field and contains real data.
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Artificial Intelligence in Modern Computer Games
Pavliska, Jiří ; Zuzaňák, Jiří (referee) ; Mikolov, Tomáš (advisor)
The aim of this bachelor's thesis is to propose an artificial inteligence that could be used to create a modern computer game. My intention is to introduce the termin Artificial Inteligence to the reader. I include the description of elements and techniques used for determining the behavior of figures that are controlled by a computer. I am also focusing the abilities of the program to search the state space and to find the shortest possible way.
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Artificial Intelligence in Strategic Computer Games
Votroubek, Lukáš ; Přibyl, Bronislav (referee) ; Zuzaňák, Jiří (advisor)
This work covers with artificial intelligence of strategy computer games, however many of these methods are usable in other areas. These are different methods used in deciding (finite state machina, fuzzy logic, Markov Process), planning (Goal-oriented action planning, Montecarlo planning, Case-based planning) and machine learning ( Reinforcement leasing, Decision Learning and Neural Networks). Objective of this thesis is to study this methods from different sources and explain their base principle. Then few of this methods resolve in more details and implement them (goal oriented planning and state machine). This thesis focuses on game engine ORTS, which is used in implementing and testing methods.
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