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Title:Drevesno preiskovanje Monte Carlo v igri Havannah
Authors:Krajnc, Vanesa (Author)
Strnad, Damjan (Mentor) More about this mentor... New window
Kohek, Štefan (Co-mentor)
Files:.pdf UN_Krajnc_Vanesa_2018.pdf (1,47 MB)
MD5: E5D128CA42A327445A0B390BDBA0B392
 
Language:Slovenian
Work type:Bachelor thesis/paper (mb11)
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V diplomskem delu predstavimo namizno igro Havannah in algoritem drevesnega preiskovanja Monte Carlo. Slednji je v zadnjih letih pripomogel k občutno boljši zmogljivosti računalniških igralcev v kompleksnih namiznih igrah s popolno informacijo, med katere spada tudi Havannah. Implementiramo tri računalniške igralce igre Havannah: prvi uporablja osnovno različico drevesnega preiskovanja Monte Carlo, drugi uporablja algoritem hitrega ocenjevanja vrednosti akcij, tretji pa kombinacijo drevesnega preiskovanja Monte Carlo s hitrim ocenjevanjem vrednosti akcij. Na koncu primerjamo vse tri igralce v medsebojnih igrah in v igrah proti človeškemu nasprotniku.
Keywords:igra na deski Havannah, drevesno preiskovanje Monte Carlo, hitro ocenjevanje vrednosti akcij, igre s popolno informacijo
Year of publishing:2018
Publisher:V. Krajnc
Source:[Maribor
UDC:004.832.2(043.2)
COBISS_ID:21891350 New window
NUK URN:URN:SI:UM:DK:ZKXMDMEM
Views:690
Downloads:114
Metadata:XML RDF-CHPDL DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:26.09.2018

Secondary language

Language:English
Title:Monte Carlo tree search in game Havannah
Abstract:In this thesis, we describe the board game Havannah and the Monte Carlo Tree Search algorithm. The latter has recently contributed to significant improvement of computer play in complex board games with perfect information, such as Havannah. We implement three computer players for Havannah: the first one using basic Monte Carlo Tree Search, the second one using Rapid Action Value Estimation algorithm and the third one using a combination of the two, called Monte Carlo Rapid Action Value Estimation. In the end, we compare the players' performances in matches against each other, as well as against a human player.
Keywords:board game Havannah, Monte Carlo tree search, Rapid Action Value Estimation, games with perfect information


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