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Arimaa
Kanis, Martin ; Škoda, Petr (referee) ; Smrž, Pavel (advisor)
Arimaa is a board game with simple rules. It is simple for human but at the same time difficult for computers. The aim of this bachelor thesis is to familiarize with game playing methods with features of the artificial intelligence. The next aim is to design and implement the program, that would be able to play against others players and programs. The most important features of the program are move generation, search and evaluation of positions. At the end, the program was tested on the game server, where played against others programs.
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Artificial Intelligence for Game Playing
Kučírek, Tomáš ; Šperka, Svatopluk (referee) ; Smrž, Pavel (advisor)
Arimaa is a strategic board game for two players. It was designed to be simple for human players and difficult for computers. The aim of this thesis is to design and implement the program with features of the artificial intelligence, which would be able to defeat human players. The implementation was realized in the three key parts: evaluation position, generation of moves and search. The program was run on the game server and defeated many bots as well as human players.
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PNS for the game Arimaa
Majerech, Ondřej ; Hric, Jan (advisor) ; Valla, Tomáš (referee)
The game of Arimaa is a strategic board game that has proved to be a challenge to computers. Not only because of its huge branching factor, but also thanks to the difficulty in creating a good evaluation function to be used with the Alpha-Beta algorithm. Proof-Number Search is an algorithm that does not depend on a heuristic evaluation function and it has been successfully applied to solving endgames of various other games. In this work, we adapt and implement the Proof-Number Search method for the game of Arimaa.
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Artificial Intelligence for Game Playing
Kučírek, Tomáš ; Šperka, Svatopluk (referee) ; Smrž, Pavel (advisor)
Arimaa is a strategic board game for two players. It was designed to be simple for human players and difficult for computers. The aim of this thesis is to design and implement the program with features of the artificial intelligence, which would be able to defeat human players. The implementation was realized in the three key parts: evaluation position, generation of moves and search. The program was run on the game server and defeated many bots as well as human players.
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Arimaa challenge - static evaluation function
Hřebejk, Tomáš ; Majerech, Vladan (advisor) ; Baudiš, Petr (referee)
Arimaa is a strategic board game for two players. It was designed with the aim that it will be hard to create a computer program that could defeat the best human players. In this thesis, we focus on the design of the static evaluation function for Arimaa. The purpose of a static evaluation function is to determine which player is leading in a given position and how significant the lead is. We have divided the problem into a few parts, which were solved separately. We paid most attention to the efficient recognition of important patterns on the board, such as goal threats. The basic element of the proposed evaluation function is mobility. For each piece, the number of steps that the piece would need to get to other places on the board is estimated. We also examined machine learning. We developed a new algorithm for learning a static evaluation function from expert games. An implementation of an Arimaa playing program, which demonstrates the proposed methods, is part of the thesis. Powered by TCPDF (www.tcpdf.org)
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Arimaa challenge - comparission study of MCTS versus alpha-beta methods
Jakl, Tomáš ; Majerech, Vladan (advisor) ; Hric, Jan (referee)
In the world of chess programming the most successful algorithm for game tree search is considered AlphaBeta search, however in game of Go it is Monte Carlo Tree Search. The game of Arimaa has similarities with both Go and Chess, but there has been no successful program using Monte Carlo Tree Search so far. The main goal of this thesis is to compare capabilities given by Monte Carlo Tree Search algorithm and AlphaBeta search, both having the same evaluation function, in the game of Arimaa.
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PNS for the game Arimaa
Majerech, Ondřej ; Hric, Jan (advisor) ; Valla, Tomáš (referee)
The game of Arimaa is a strategic board game that has proved to be a challenge to computers. Not only because of its huge branching factor, but also thanks to the difficulty in creating a good evaluation function to be used with the Alpha-Beta algorithm. Proof-Number Search is an algorithm that does not depend on a heuristic evaluation function and it has been successfully applied to solving endgames of various other games. In this work, we adapt and implement the Proof-Number Search method for the game of Arimaa.
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Arimaa
Kanis, Martin ; Škoda, Petr (referee) ; Smrž, Pavel (advisor)
Arimaa is a board game with simple rules. It is simple for human but at the same time difficult for computers. The aim of this bachelor thesis is to familiarize with game playing methods with features of the artificial intelligence. The next aim is to design and implement the program, that would be able to play against others players and programs. The most important features of the program are move generation, search and evaluation of positions. At the end, the program was tested on the game server, where played against others programs.
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