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* [[Kunihito Hoki]], [[Tomoyuki Kaneko]], [[Akihiro Kishimoto]], [[Takeshi Ito]] ('''2013'''). ''Parallel Dovetailing and its Application to Depth-First Proof-Number Search''. [[ICGA Journal#36_1|ICGA Journal, Vol. 36, No. 1]] <ref>[https://en.wikipedia.org/wiki/Dovetailing_%28computer_science%29 Dovetailing (computer science) from Wikipedia]</ref>
* [[Kunihito Hoki]], [[Tomoyuki Kaneko]], [[Daisaku Yokoyama]], [[Takuya Obata]], [[Hiroshi Yamashita]], [[Yoshimasa Tsuruoka]], [[Takeshi Ito]] ('''2013'''). ''[https://ieeexplore.ieee.org/document/6598505/ A System-Design Outline of the Distributed-Shogi-System Akara 2010]''. [https://dblp.uni-trier.de/db/conf/snpd/snpd2013.html SNPD 2013]
* [[Kunihito Hoki]], [[Tomoyuki Kaneko]] ('''2014'''). ''[https://www.jair.org/papers/paper4217.html Large-Scale Optimization for Evaluation Functions with Minimax Search]''. [https://www.jair.org/vol/vol49.html JAIR Vol. 49], [https://wwwpdfs.jairsemanticscholar.org/mediaeb9c/4217/live-4217-7792-jair173576577acbb8800bf96aba452d77f1dc19.pdf pdf] » [[Automated Tuning]], [[Shogi]] <ref>[http://www.talkchess.com/forum/viewtopic.php?t=55084 MMTO for evaluation learning] by [[Jon Dart]], [[CCC]], January 25, 2015</ref>
==2015 ...==
* [[Yusaku Mandai]], [[Tomoyuki Kaneko]] ('''2015'''). ''LinUCB Applied to Monte Carlo Tree Search''. [[Advances in Computer Games 14]]
* [[Shogo Takeuchi]], [[Tomoyuki Kaneko]] ('''2015'''). ''[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7336038 Estimating Ratings of Computer Players by the Evaluation Scores and Principal Variations in Shogi]''. [http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7335993 ACIT-CSI]
* [[Takahisa Imagawa]], [[Tomoyuki Kaneko]] ('''2016'''). ''Monte Carlo Tree Search with Robust Exploration''. [[CG 2016]]
* [[Taichi Nakayashiki]], [[Tomoyuki Kaneko]] ('''2018'''). ''Learning of Evaluation Functions via Self-Play Enhanced by Checkmate Search''. [[TAAI 2018]]
* [[Yusaku Mandai]], [[Tomoyuki Kaneko]] ('''2018'''). ''Alternative Multitask Training for Evaluation Functions in Game of Go''. [[TAAI 2018]]
* [[Hanhua Zhu]], [[Tomoyuki Kaneko]] ('''2018'''). ''Comparison of Loss Functions for Training of Deep Neural Networks in Shogi''. [[TAAI 2018]]
* [[Tianhe Wang]], [[Tomoyuki Kaneko]] ('''2018'''). ''Application of Deep Reinforcement Learning in Werewolf Game Agents''. [[TAAI 2018]]
* [[Hyunwoo Oh]], [[Tomoyuki Kaneko]] ('''2018'''). ''Deep Recurrent Q-Network with Truncated History''. [[TAAI 2018]]
* [[Yusaku Mandai]], [[Tomoyuki Kaneko]] ('''2019'''). ''RankNet for evaluation functions of the game of Go''. [[ICGA Journal#41_2|ICGA Journal, Vol. 41, No. 2]]
* [[Tomoyuki Kaneko]], [[Takenobu Takizawa]] ('''2019'''). ''[https://www.semanticscholar.org/paper/Computer-Shogi-Tournaments-and-Techniques-Kaneko-Takizawa/caa062c0d95f15c85251351b20cdd80a2a0e1b82#paper-header Computer Shogi Tournaments and Techniques]''. [[IEEE#TOG|IEEE Transactions on Games]], Vol. 11
=External Links=
=References=
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[[Category:Researcher|Kaneko]]
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