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Model of a Betting Office
Matúška, Peter ; Zbořil, František (referee) ; Grulich, Lukáš (advisor)
Document analyses the betting office as economic subject. It shows how to make its model good to watch economic properties of this subject including commercial and other influence on customers. It also shows implementation of this model in C++ programming language with SIMLIB simulation library and results of simulating and experiments with this model.
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Support for Searching in Parish Books
Reisenauer, Klára ; Zbořil, František (referee) ; Rozman, Jaroslav (advisor)
This master's thesis deals with analysis, design and implementation of a web-based information system for support in searching in Parish Books. The given information system automatically generates notes according to imported GEDCOM file. These notes are stored in database and can be edited or removed. At the same time, the possible way to display geographic data of specific Parish Books on the map was analysed and designed, and will~be later implemented in cooperation with existing information system Geowiki .
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Interconnection of Recent Strategic Games with Multi-Agent Frameworks
Válek, Lukáš ; Kočí, Radek (referee) ; Zbořil, František (advisor)
This thesis is focused on design of framework for creation an articial opponents in strategy games. We will analyze different types of strategy games and artificial intelligence systems used in these types of games. Next we will describe problems, which can occur in these systems and why agent-based systems makes better artificial opponents. Next we will use knowledge from this research to design and implement framework, which will act as support for creating an artificial intelligence in strategy games.
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Intelligent Reactive Agent for the Game Ms.Pacman
Bložoňová, Barbora ; Zbořil, František (referee) ; Drahanský, Martin (advisor)
This thesis focuses on artificial intelligence for difficult decision problemes such as the game with uncertainty Ms. Pacman. The aim of this work is to design and implement intelligent reactive agent using a method from the field of reinforcement learning, demonstrate it on visual demo Ms.Pacman and compare its intelligence with well-known informed methods of playing games (Minimax, AlfaBeta Pruning, Expectimax). The thesis is primarily structured into two parts. The theoretical part deals with adversarial search (in games), reactivity of agent and possibilities of machine learning, all in the context of Ms. Pacman. The second part addresses the design of agent's versions behaviour implementation and finally its comparison to other methods of adversarial search problem, evaluation of results and a few ideas for future improvements.
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Applet for Playing the Go Game
Dosoudil, Jan ; Zbořil, František (referee) ; Křena, Bohuslav (advisor)
This bachelor thesis deals with development of a Java applet for playing the board game of Go against computer as well as for playing Go by two human players connected by the Internet. The applet does not implement artificial intelligence for ruling and playing the game, however, it exploits an external Go engine trough the Go Text Protocol (GTP). The game of Go is probably the most complex board game and implementation of the engine is out of the scope of this thesis. The game of Go is not well know in Europe, so, there is given a brief introduction to history and rules of Go for the reader at the beginning of the thesis.
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Social Networking for Questionnaire Survays
Huvar, Lukáš ; Zbořil, František (referee) ; Hrubý, Martin (advisor)
The aim of this work is to design and implement an application using an experimental library CloudKit. This application will serve as a social network for community submitters and questionnaire surveys respondents. Implemented social network is tested on a group of users who are involved in running the network. The benefit of this work is to test the Library CloudKit and its relevance for social networks.
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Robot for Robotour 2010
Kubát, David ; Zbořil, František (referee) ; Rozman, Jaroslav (advisor)
The objective of this master's thesis was to get acquainted with an autonomous outdoor robot competition - The Robotour and further to study the capabilities and information about a robot designed on the DITS FIT Brno VUT. Next part of the project was to study various planning and localization algorithms and to make a proposal of a functional solution, allowing the robot to participate in the competition. To be specific, the goal of this work was to use the acquired knowledge for implementation of an antonomous software so the robot can start in the year 2010 race. The solution also included several related mechanical modifications. The final solution fulfills all the competiton rules and is capable of taking part in this year's plant.
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Multirobot Path Planning in a Dynamic System
Dokoupil, Ladislav ; Veigend, Petr (referee) ; Zbořil, František (advisor)
This thesis deals with the problem of dynamic environment search using multi-agent systems. The primary result of this work is participation in the MAPC2022 contest, but the application can be found in the exploration of unknown space, assuming finite visibility and unlimited distance of communication of the agents. After describing the current methods for solving the given problem and their limitations, an algorithm based on ant colony optimization is proposed. Graphs were then created with data from running program with various parameters. The result of work is agents synchronization improvements and overall optimization of the platform involved in the mentioned contest from previous year. As a result half more of explored space was measured compared to previous solution.
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Strategic Game with Uncertainity
Sova, Michal ; Zbořil, František (referee) ; Zbořil, František (advisor)
The thesis focuses on creating an autonomous system for the game Scotland Yard by using machine learning method. The problem is solved by algorithm Monte Carlo tree search. Algorithm Monte Carlo tree search was tested against algorithm Alpha-beta. These results showed that Monte Carlo tree search algorithm is operational but win rate of this algorithm is lower than win rate of algorithm Alpha-beta. The resulting system is functional, autonomous and capable of playing the game Scotland Yard on simplified game area. There was an attempt to expand simplified version of the game Scotland Yard. In expanded version algorithm Alpha-beta was not successful because of insufficient computational resources. Algorithm Monte Carlo tree search, on the other hand, was more successful in expanded version.
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