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Artificial intelligence for Sushi Go!
 Filek, Jiří ; Holan, Tomáš (advisor) ; Mráz, František (referee)
The thesis deals with an artificial intelligence for a Sushi Go! card game. It is a game with simultaneous moves for two to five players. The thesis presents multiple approaches for development of an artificial intelligence. The main focus is on methods based on the MCTS algorithm, namely DUCT and EXP3. An artificial intelligence using weighted rules is tried as well. The weights are assigned by a genetic algorithm. The first part of the thesis is about game analysis and description of chosen methods. The second part of the thesis is about parameter tuning and comparison of different agents for two or more players. The comparison is based on a large number of games played between agents. The last part of the thesis deals with an implementation. A graphical and a console applications were created for the purpose of developing an artificial intelligence. The console application is used for parameter tuning and also to compare artificial intelligences. The graphical application is used for a game of human against artificial intelligence or other humans on a single computer. Overall, DUCT performs best in every experiment despite its theoretical disadvantages.
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