Difference between revisions of "Kristallweizen"

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(Created page with "'''Home * Engines * Kristallweizen''' FILE:Hefeweizen and kristallweizen.jpg|border|right|thumb| Kristallweizen and Hefeweizen (right) <ref>A [https://com...")
 
 
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'''[[Main Page|Home]] * [[Engines]] * Kristallweizen'''
 
'''[[Main Page|Home]] * [[Engines]] * Kristallweizen'''
  
[[FILE:Hefeweizen and kristallweizen.jpg|border|right|thumb| Kristallweizen and Hefeweizen (right) <ref>A [https://commons.wikimedia.org/wiki/File:Hefeweizen_and_kristallweizen.jpg photograph] of two varieties of [https://en.wikipedia.org/wiki/Wheat_beer wheat beer]: Kristallweizen (left) and Hefeweizen (right), filtered and unfiltered [https://en.wikipedia.org/wiki/Beer_in_Germany German wheat beers]</ref> ]]  
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[[FILE:Hefeweizen and kristallweizen.jpg|border|right|thumb| Kristallweizen and Hefeweizen (right) <ref>A [https://commons.wikimedia.org/wiki/File:Hefeweizen_and_kristallweizen.jpg photograph] of two varieties of [https://en.wikipedia.org/wiki/Wheat_beer wheat beer]: Kristallweizen (left) and Hefeweizen (right), filtered and unfiltered [https://en.wikipedia.org/wiki/Beer_in_Germany German wheat beers]</ref> <ref>[https://en.wikipedia.org/wiki/Erdinger Erdinger from Wikipedia]</ref> ]]  
  
 
'''Kristallweizen''',<br/>
 
'''Kristallweizen''',<br/>
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=Hefeweizen=
 
=Hefeweizen=
Kristallweizen's forerunner, the more unfiltered '''Hefeweizen''' uses an [[Apery]] type of KPP/KKP indexed [[Piece-Square Tables|Piece-Square Tables]] approach, initially introduced by [[Bonanza]],
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Kristallweizen's forerunner, the more unfiltered '''Hefeweizen''' uses an [[Apery]] type of KPP/KKP indexed [[Piece-Square Tables|Piece-Square Tables]] approach, initially introduced by [[Bonanza]].
 
Hefeweizen won the [[WCSC28]] in 2018, also on the [https://en.wikipedia.org/wiki/Amazon_Elastic_Compute_Cloud Amazon Elastic Compute Cloud] with [[Pondering|multi ponder]] <ref>[http://www2.computer-shogi.org/wcsc28/ 第28回世界コンピュータ将棋選手権 - 28th World Computer Shogi Championship]</ref>.
 
Hefeweizen won the [[WCSC28]] in 2018, also on the [https://en.wikipedia.org/wiki/Amazon_Elastic_Compute_Cloud Amazon Elastic Compute Cloud] with [[Pondering|multi ponder]] <ref>[http://www2.computer-shogi.org/wcsc28/ 第28回世界コンピュータ将棋選手権 - 28th World Computer Shogi Championship]</ref>.
  
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==Shogi Engine==
 
==Shogi Engine==
 
* [https://github.com/Tama4649/Kristallweizen/ GitHub - Tama4649/Kristallweizen: 第29回世界コンピュータ将棋選手権 準優勝のKristallweizenです。]
 
* [https://github.com/Tama4649/Kristallweizen/ GitHub - Tama4649/Kristallweizen: 第29回世界コンピュータ将棋選手権 準優勝のKristallweizenです。]
* [http://sizer.main.jp/wcsc29/services/kristallweizen/ ristallweizen – 第29回世界コンピュータ将棋選手権 (wcsc29)]
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* [http://sizer.main.jp/wcsc29/services/kristallweizen/ Kristallweizen – 第29回世界コンピュータ将棋選手権 (wcsc29)]
 
==Misc==
 
==Misc==
 
* [https://en.wikipedia.org/wiki/Wheat_beer Wheat beer from Wikipedia]
 
* [https://en.wikipedia.org/wiki/Wheat_beer Wheat beer from Wikipedia]

Latest revision as of 14:15, 30 September 2020

Home * Engines * Kristallweizen

Kristallweizen and Hefeweizen (right) [1] [2]

Kristallweizen,
a Shogi engine, or more precisely a Shogi evaluation function by team Barrel house, a beer bar in front of the Okayama station [3], due to the developers around Seiji Shiba, Mitsunori Matsushita and Yasuhiro Tajima [4]. Kristallweizen became runner-up at the WCSC29 in 2019, where it run in the Amazon Elastic Compute Cloud and applied multi pondering. Kristallweizen is a NNUE HalfKP-256x2-32-32 type of evaluation function, used within YaneuraOu's search, a Shogi adaptation of Stockfish's search. Further CSA available engines and libraries used to train and prepare Kristallweizen mentioned on the WCSC29 site [5] were Apery, Tanuki, Qhapaq, Elmo, dlshogi [6], python-shogi [7] and the Android Go Player No. 18 [8]. Kristallweizen may also used with Dolphin, also based on YaneuraOu's (version 4.82) search [9] [10].

Hefeweizen

Kristallweizen's forerunner, the more unfiltered Hefeweizen uses an Apery type of KPP/KKP indexed Piece-Square Tables approach, initially introduced by Bonanza. Hefeweizen won the WCSC28 in 2018, also on the Amazon Elastic Compute Cloud with multi ponder [11].

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