Reinforcement Learning for the Game of Battleship – Tomáš Kancko
Tomáš Kancko
Bachelor's thesis
Reinforcement Learning for the Game of Battleship
Reinforcement Learning for the Game of Battleship
Abstract:
Bakalárska práca rozoberá využiteľnosť heuristík a vyhľadávacích algoritmov na hre Battleship. Prvá časť obsahuje všeobecný prehľad o hre. Druhá časť sa skladá z analýzy a implementácie rôznych heuristík a porovnáva ich. Tretia časť rozoberá MCTS a jeho parametre, formuláciu (PO)MDP modelu. V poslednej časti sa nachádza vyhodnotenie a porovnanie všetkých metód.Abstract:
The thesis explores the usability of general heuristic search algorithms in the Battleship domain. The first part of the thesis is an overview of the Battleship game. The second part analyses different designs, patterns and implementations of several heuristics and compares them. The third part is an overview of the MCTS algorithm and its parameters. The thesis also contains an outline of the formulation …more
Language used: English
Date on which the thesis was submitted / produced: 20. 7. 2020
Identifier:
https://is.muni.cz/th/oupp1/
Thesis defence
- Date of defence: 25. 9. 2020
- Supervisor: RNDr. Petr Novotný, Ph.D.
- Reader: Mgr. Jiří Vahala
Citation record
Full text of thesis
Contents of on-line thesis archive
Published in Theses:- světu
Other ways of accessing the text
Institution archiving the thesis and making it accessible: Masarykova univerzita, Fakulta informatikyMasaryk University
Faculty of InformaticsBachelor programme / field:
Applied Informatics / Applied Informatics
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