Difference between revisions of "Kristallweizen"
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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]] | + | 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>. | ||
Revision as of 15:15, 30 September 2020
Home * Engines * Kristallweizen
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].
Forum Posts
- The Stockfish of shogi by Larry Kaufman, CCC, January 07, 2020
- Dolphin software by Larry Kaufman, SHOGI-L, February 02, 2020
External Links
Shogi Engine
- 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。
- ristallweizen – 第29回世界コンピュータ将棋選手権 (wcsc29)
Misc
References
- ↑ A photograph of two varieties of wheat beer: Kristallweizen (left) and Hefeweizen (right), filtered and unfiltered German wheat beers
- ↑ Erdinger from Wikipedia
- ↑ Beer Bar Barrel house - Facebook
- ↑ The 29th World Computer Shogi Championship Applicant List by Reijer Grimbergen on behalf of Takenobu Takizawa, SHOGI-L, February 03, 2019
- ↑ 第29回世界コンピュータ将棋選手権 - 29th World Computer Shogi Championship
- ↑ GitHub - TadaoYamaoka/python-dlshogi
- ↑ GitHub - gunyarakun/python-shogi: A pure Python shogi library with move generation and validation and handling of common formats.
- ↑ 人造棋士１８号 - django-\/\/ i K | Android Go Player No.18
- ↑ Re: Strongest free shogi engine? by km0010, Reddit
- ↑ 使用ソフト | shogi-engines
- ↑ 第28回世界コンピュータ将棋選手権 - 28th World Computer Shogi Championship
