TY - GEN
T1 - Technique analysis and designing of program with UCT algorithm for NoGo
AU - Li, Rui
AU - Wu, Yueqiu
AU - Zhang, Andi
AU - Ma, Chen
AU - Chen, Bo
AU - Wang, Shuliang
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2013
Y1 - 2013
N2 - As a typical example of dynamic search algorithm, the UCT algorithm was initially used on the computerized game of GO. This paper briefly introduces the Markov Decision process, the Multi-armed Bandit model, and the Upper-Confidence Bandit formula. It analyzes the source and structure of the UCT algorithm in theory, and proves that the UCT algorithm is suitable for the design of the program of NoGo. According to the characteristics of NoGo, in the paper we improved the algorithm in terms of move generation and data reuse. We also tried to establish an off-line knowledge database for research. With experimental data we have tested and evaluated the above methods. The above algorithm and technology have been successfully used in WTShadows the NoGo game program, which enabled us to have won the champion in national competition. © 2013 IEEE.
AB - As a typical example of dynamic search algorithm, the UCT algorithm was initially used on the computerized game of GO. This paper briefly introduces the Markov Decision process, the Multi-armed Bandit model, and the Upper-Confidence Bandit formula. It analyzes the source and structure of the UCT algorithm in theory, and proves that the UCT algorithm is suitable for the design of the program of NoGo. According to the characteristics of NoGo, in the paper we improved the algorithm in terms of move generation and data reuse. We also tried to establish an off-line knowledge database for research. With experimental data we have tested and evaluated the above methods. The above algorithm and technology have been successfully used in WTShadows the NoGo game program, which enabled us to have won the champion in national competition. © 2013 IEEE.
KW - Dynamic Move Queue
KW - Knowledge Base
KW - MAB Model
KW - Markov Decision Process
KW - NoGo
KW - UCT Algorithm
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84882767049&origin=recordpage
U2 - 10.1109/CCDC.2013.6561055
DO - 10.1109/CCDC.2013.6561055
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781467355322
T3 - 2013 25th Chinese Control and Decision Conference, CCDC 2013
SP - 923
EP - 928
BT - 2013 25th Chinese Control and Decision Conference, CCDC 2013
T2 - 2013 25th Chinese Control and Decision Conference, CCDC 2013
Y2 - 25 May 2013 through 27 May 2013
ER -