Thesis Details
Strategická desková hra s neurčitostí
This thesis focuses on the implementation of a system for playing the board game Scotland Yard autonomously and also focuses on a comparison of this system with similar ones. I focused on obtaining enough information about the possible methods that should be suitable for such a system and decided to implement this system using the Monte Carlo Tree Search method. The result implementation of the system was tested against similar systems, achieving an excellent result against another system that used an equivalent method. There was achieved a balanced result against a system that used the Alpha-Beta method. The main result of this work is a working version of an autonomous system for playing the game Scotland Yard on a reduced field. It also provides the possibility of using two similar systems within a single program in order to compare their implementations.
board games, strategy games, games with uncertainty, Scotland Yard, Monte Carlo Tree Search, autonomous gaming, control algorithms, machine learning, gaming methods
Bařina David, Ing., Ph.D. (DCGM FIT BUT), člen
Hynek Jiří, Ing., Ph.D. (DIFS FIT BUT), člen
Kekely Lukáš, Ing., Ph.D. (DCSY FIT BUT), člen
Rogalewicz Adam, doc. Mgr., Ph.D. (DITS FIT BUT), člen
@bachelorsthesis{FITBT24711,
author = "Martin Ger\v{z}a",
type = "Bachelor's thesis",
title = "Strategick\'{a} deskov\'{a} hra s neur\v{c}itost\'{i}",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2022,
location = "Brno, CZ",
language = "czech",
url = "https://www.fit.vut.cz/study/thesis/24711/"
}