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Shogi

291 bytes added, 18:40, 7 January 2021
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'''Shogi''' (Japanese Chess),<br/>
a chess variant that evolved directly from [[Shatranj]], just like the western [[Chess|chess]]. It is played on 9x9 board. Compared to chess, Shogi pieces have limited mobility, but this is compensated by the fact that captured enemy pieces can be [[Piece Drop|dropped]] on the board as one's own. This leads to the wild, tactical game. Shogi has greater [[Branching Factor|branching factor]] than chess. Development of Shogi programs has taken slightly different route than in chess programming. The stress is on [[Pattern Recognition|pattern recognition]] and [[Selectivity|selective search]] techniques. However, with the advent of [[NNUE]] <ref>[[Yu Nasu]] ('''2018'''). ''&#398;U&#1048;&#1048; Efficiently Updatable Neural-Network based Evaluation Functions for Computer Shogi''. Ziosoft Computer Shogi Club, [https://github.com/ynasu87/nnue/blob/master/docs/nnue.pdf pdf] (Japanese with English abstract)[https://github.com/asdfjkl/nnue GitHub - asdfjkl/nnue translation]</ref> along with adaptations of [[Stockfish]] to Shogi such as [[YaneuraOu]] <ref>[https://github.com/yaneurao/YaneuraOu GitHub - yaneurao/YaneuraOu: YaneuraOu is the World's Strongest Shogi engine(AI player), WCSC29 1st winner, educational and USI compliant engine]</ref>, and [[Kristallweizen]] <ref>[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。]</ref>, and the consequent [[Stockfish NNUE]] hype <ref>[http://www.talkchess.com/forum3/viewtopic.php?f=2&t=74059 Stockfish NN release (NNUE)] by [[Henk Drost]], [[CCC]], May 31, 2020</ref>, both worlds seem to reunite again.
=Pieces & Moves=
* [[David Silver]], [[Thomas Hubert]], [[Julian Schrittwieser]], [[Ioannis Antonoglou]], [[Matthew Lai]], [[Arthur Guez]], [[Marc Lanctot]], [[Laurent Sifre]], [[Dharshan Kumaran]], [[Thore Graepel]], [[Timothy Lillicrap]], [[Karen Simonyan]], [[Demis Hassabis]] ('''2017'''). ''Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm''. [https://arxiv.org/abs/1712.01815 arXiv:1712.01815] » [[AlphaZero]]
'''2018'''
* [[Yu Nasu]] ('''2018'''). ''&#398;U&#1048;&#1048; Efficiently Updatable Neural-Network based Evaluation Functions for Computer Shogi''. Ziosoft Computer Shogi Club, [https://github.com/ynasu87/nnue/blob/master/docs/nnue.pdf pdf], [https://www.apply.computer-shogi.org/wcsc28/appeal/the_end_of_genesis_T.N.K.evolution_turbo_type_D/nnue.pdf pdf] (Japanese with English abstract)[https://github.com/asdfjkl/nnue GitHub - asdfjkl/nnue translation] <ref>[http://www.talkchess.com/forum3/viewtopic.php?f=2&t=76250 Translation of Yu Nasu's NNUE paper] by [[Dominik Klein]], [[CCC]], January 07, 2021</ref>
* [[Takafumi Nakamichi]], [[Takeshi Ito]] ('''2018'''). ''Adjusting the evaluation function for weakening the competency level of a computer shogi program''. [[ICGA Journal#40_1|ICGA Journal, Vol. 40, No. 1]]
* [[David Silver]], [[Thomas Hubert]], [[Julian Schrittwieser]], [[Ioannis Antonoglou]], [[Matthew Lai]], [[Arthur Guez]], [[Marc Lanctot]], [[Laurent Sifre]], [[Dharshan Kumaran]], [[Thore Graepel]], [[Timothy Lillicrap]], [[Karen Simonyan]], [[Demis Hassabis]] ('''2018'''). ''[http://science.sciencemag.org/content/362/6419/1140 A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play]''. [https://en.wikipedia.org/wiki/Science_(journal) Science], Vol. 362, No. 6419 <ref>[https://deepmind.com/blog/alphazero-shedding-new-light-grand-games-chess-shogi-and-go/ AlphaZero: Shedding new light on the grand games of chess, shogi and Go] by [[David Silver]], [[Thomas Hubert]], [[Julian Schrittwieser]] and [[Demis Hassabis]], [[DeepMind]], December 03, 2018</ref>

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