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Permanent link (DOI): https://doi.org/10.7939/R3GH9BG82

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TDS+: Improving Temperature Discovery Search Open Access

Descriptions

Other title
Subject/Keyword
game tree search
TDS+
Amazons
combinatorial game theory
Temperature Discovery Search
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Zhang, Yeqin
Supervisor and department
Müller, Martin (Computing Science)
Examining committee member and department
Hayward, Ryan (Computing Science)
Friggstad, Zachary (Computing Science)
Müller, Martin (Computing Science)
Department
Department of Computing Science
Specialization

Date accepted
2015-01-20T14:05:47Z
Graduation date
2015-06
Degree
Master of Science
Degree level
Master's
Abstract
Temperature Discovery Search (TDS) is a forward search method for computing or approximating the temperature of a combinatorial game. Temperature and mean are important concepts in combinatorial game theory, which can be used to develop efficient algorithms for playing well in a sum of subgames. A new algorithm TDS+ with five enhancements of TDS is developed, which greatly speeds up both exact and approximate versions of TDS. Means and temperatures can be computed faster, and fixed-time approximations which are important for practical play can be computed with higher accuracy than before.
Language
English
DOI
doi:10.7939/R3GH9BG82
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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