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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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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 I chose for my study is SARSA, short for State Action Reward State Action algorithm. It is a modified version of algorithm named Q-Learning. I compared SARSA with other algorithms by letting them play against each other in application that I made in Unity Engine. Algorithms that I compared to SARSA are Q-Learning and Counterfactual Regret Minimization. I achieved a 69,147\,\% win ratio in a game against Q-Learning. In games against Counterfactual Regret Minimization it was only 29,84\,\% win ratio. The main outcome of this study is that SARSA, modified version of Q-Learning is effective against Q-Learning algorithm. On the other hand the SARSA algorithm was very ineffective against the Counterfactual Regret Minimization algorithm.
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Effective Dynamic Programming in Bioinformatics
Franěk, Jaromír ; Hynek, Jiří (referee) ; Burgetová, Ivana (advisor)
Purpose of this thesis is to study principle of effective algorithms, that are using dynamic programming. Using this knowledge to create application demonstrating principle of effective algorithm of dynamic programming in bioinformatics and write a report summarizing results. Algorithms used in this thesis are solving DNA sequence alignment or RNA secondary structure prediction. These algorithms are compared between themselves based on different input values. For DNA sequence alignment are used algorithms such as Needleman-Wunch and X-drop. For prediction of secondary RNA structure is used Zuker algorithm, that should remove some of Nussin algorithm weaknesses and Nussin algorithm itself. Recursion is showed by recursion trees. Dynamic programming is showed by score matrix. User also have ability to compare speed of both approaches for given sequences. It is programmed as web application, that run on client's side. This ensure easy availability.
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Dynamic Programming in Graph Algorithms
Biloš, Martin ; Křivka, Zbyněk (referee) ; Burgetová, Ivana (advisor)
This work is about graph algorithms, their use and the benefit of the optimization method of dynamic programming. This benefit is show to the user via the graphic application. Graph algorithms find use in many sectors of human activity. They are used in packet routing or, for example, navigation. There are three methods of graph algorithms used in this work. This problems are solved with classic and dynamic way and measured data are compared.
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Optimal path planning for electric vehicles
Horák, Filip ; Šoustek, Petr (referee) ; Kůdela, Jakub (advisor)
This master’s thesis is about optimal route planning for electric vehicles. The first, theoretical part of this work introduces the issue and describes several heuristic methods that have been used to address optimization tasks. A practical part of the thesis is based around software implementation of the methods described earlier. Finally, several experiments and comparisons of obtained results are carried out.
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The Shortest Graph's Pahts Finding
Jágr, Petr ; Ohlídal, Miloš (referee) ; Jaroš, Jiří (advisor)
The aim of this thesis is finding, comparing and implementation of algorithms for finding the shortest paths between each of pairs of nodes in a graph. For this task I use modifications of existing algorithms to achive the lowest time consumption of the computation. Modifications are established on Dijkstra's and Floyd-Warshall's algorithm. We also familiarize with Bellman-Ford algorithm.
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Network Protocols Semiautomatic Diagnostics
Svoboda, Ondřej ; Ryšavý, Ondřej (referee) ; Holkovič, Martin (advisor)
This thesis is about semiautomatic network protocol diagnostics and creating protocol description from eavesdropped communication. Several network eavesdropping techniques and some common programs for network analysis are introduced. Well-known network protocols are described, with focus on their communication messages. Some already existing methods for creating models from examples are mentioned and their characteristics defined. Next we design architecture of developed tool and some methods, that create protocol description. After that we explain implementation of this tool and finally the tool is tested and experimented with.
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Query-by-Example Keyword Spotting
Skácel, Miroslav ; Hannemann, Mirko (referee) ; Szőke, Igor (advisor)
Tato diplomová práce se zabývá moderními přístupy detekce klíčových slov a detekce frází v řečových datech. V úvodní části je seznámení s problematikou a teoretický popis metod pro detekci. Následuje popis reprezentace vstupních datových sad použitých při experimentech a evaluaci. Dále jsou uvedeny metody pro detekci klíčových slov definovaných vzorem. Následně jsou popsány evaluační metody a techniky použité pro skórování. Po provedení experimentů na datových sadách a po evaluaci jsou diskutovány výsledky. V dalším kroku jsou navrženy a poté implementovány moderní postupy vedoucí k vylepšení systému pro detekci a opět je provedena evaluace a diskuze dosažených výsledků. V závěrečné části je práce zhodnocena a jsou zde navrženy další směy vývoje našeho systému. Příloha obsahuje manuál pro používání implementovaných skriptů.
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Clustering of Protein Sequences Based on Primary Structure of Proteins
Jurásek, Petr ; Stryka, Lukáš (referee) ; Burgetová, Ivana (advisor)
This master's thesis consider clustering of protein sequences based on primary structure of proteins. Studies the protein sequences from they primary structure. Describes methods for similarities in the amino acid sequences of proteins, cluster analysis and clustering algorithms. This thesis presents concept of distance function based on similarity of protein sequences and implements clustering algorithms ANGES, k-means, k-medoids in Python programming language.
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