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Theses and Dissertations

Playing and Solving Havannah Open Access

Descriptions

Other title
Subject/Keyword
rave
Games
AI
computer games
Monte-Carlo
solving games
board games
artificial intelligence
MCTS
Havannah
Monte-Carlo Tree Search
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Ewalds, Timo V
Supervisor and department
Ryan Hayward (Computing Science)
Jonathan Schaeffer (Computing Science)
Examining committee member and department
Martin Mueller (Computing Science)
Mazi Shirvani (Mathematics)
Department
Department of Computing Science
Specialization

Date accepted
2011-12-21T14:56:34Z
Graduation date
2012-06
Degree
Master of Science
Degree level
Master's
Abstract
Havannah is a recent game that is interesting from an AI research perspective. Some of its properties, including virtual connections, frames, dead cells, draws and races to win, are explained. Monte Carlo Tree Search (MCTS) is well suited to play Havannah, but many improvements are possible. Several forms of heuristic knowledge in the tree show playing strength gains, and a change to the rules in the rollout policy significantly improves play on larger board sizes. Together, a greater than 80 winning rate, or 300 elo gain, is achieved on all board sizes over an already fairly strong player. This MCTS player is augmented with a few engineering improvements, such as threading, memory management and early draw detection, and then used to solve all 6 openings of size 4 Havannah, a game with a state space on the order of 6x10^15 states. Castro, the implementation and test bed, is released open source.
Language
English
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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