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	Artificial intelligence for the Game Carcassonne: The Discovery Motlíček, Ondřej ; Hric, Jan (advisor) ; Zelinka, Mikuláš (referee) The bachelor paper deals with the development of an artificial intelligence for the game Carcassonne - The Discovery. Different approaches for designing an artificial intel- ligence are presented. Heuristic functions based on various aspects of the game. Monte Carlo methods and the Expectiminimax algorithm are used for state space of the game. The designed methods are implemented and experimentally tested and compared by simulations of the game between the artificial players. Results of the experiment are pre- sented and explained. The simulation environment consists of multiple programs for the game simulation of both artificial and human players. A batch simulation of the artificial intelligence is emphasized. 1 Detailed record
	Applications of Markov chains Berdák, Vladimír ; Beneš, Viktor (advisor) ; Kadlec, Karel (referee) The goal of the thesis is the use of Markov chains and applying them to algorithms of the method Monte Carlo. Necessary theory of Markov chains is introduced and we are aiming to understand stationary distribution. Among MCMC methods the thesis is focused on Gibbs sampler which we apply to the hard-core model. We subsequently simulate distribution of ones and zeros on vertices of a graph. Statistical characteristics of the number of ones are estimated from realizations of MCMC and presented in figures. Detailed record
	Oceňování opcí pomocí Monte Carlo metod Waldeckerová, Naďa ; Witzany, Jiří (advisor) ; Vacek, Vladislav (referee) This thesis aims to analyse different Monte Carlo methods when applied to the problem of option pricing. Closer attention is paid to three variance reduction techniques, namely control variathes, importance sampling and antithetic variables, and two different approaches, least-squares Monte Carlo and quasi-Monte Carlo methods. The detailed analysis of the differences and improvements is done on a problem of plain vanilla option pricing. At the end the methods are each applied to valuation of different exotic options. Detailed record

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