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Shogi

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* [[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>
* [[Hanhua Zhu]], [[Tomoyuki Kaneko]] ('''2018'''). ''Comparison of Loss Functions for Training of Deep Neural Networks in Shogi''. [https://dblp.uni-trier.de/db/conf/taai/taai2018.html TAAI 2018]
* [[Shogo Takeuchi]] ('''2018'''). ''Weighted Majority Voting with a Heterogeneous System in the Game of Shogi''. [https://dblp.uni-trier.de/db/conf/taai/taai2018.html TAAI 2018]

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