Kunihito+Hoki

a Japanese chemist, computer scientist, and since 2010 Assistant Professor at the [|University of Electro-Communications]. Kunihito Hoti received a [|D.Sc.] in [|Chemistry] from [|Tohoku University], and has been a research fellow at the University of Toronto as well as Tohoku University, where he then became Assistant Professor. As Shogi programmer, he is author of the strong Shogi program [|Bonanza], famous for its supervised move adaption tuning method called Minimax Tree Optimization (MMTO), also dubbed the **Bonanza-Method**. || toc =Selected Publications=
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 * [[image:kunihito_hoki.jpg link="http://tedxkidschiyoda.com/speakers/243"]] ||~ || **Kunihito Hoki**,
 * Kunihito Hoki ||~ ||^ ||
 * Kunihito Hoki (**2006**). //Optimal control of minimax search result to learn positional evaluation//. 11th Game Programming Workshop (Japanese)
 * Takuya Obata, Takuya Sugiyama, Kunihito Hoki, Takeshi Ito (**2010**). //[|Consultation Algorithm for Computer Shogi: Move Decisions by Majority]//. CG 2010
 * Takuya Sugiyama, Takuya Obata, Kunihito Hoki, Takeshi Ito (**2010**). //[|Optimistic Selection Rule Better Than Majority Voting System]//. CG 2010
 * Tomoyuki Kaneko, Kunihito Hoki (**2011**). //Analysis of Evaluation-Function Learning by Comparison of Sibling Nodes//. Advances in Computer Games 13
 * Kunihito Hoki, Tomoyuki Kaneko (**2011**). //The Global Landscape of Objective Functions for the Optimization of Shogi Piece Values with a Game-Tree Search//. Advances in Computer Games 13
 * Kunihito Hoki, Tomoyuki Kaneko, Akihiro Kishimoto, Takeshi Ito (**2013**). //Parallel Dovetailing and its Application to Depth-First Proof-Number Search//. ICGA Journal, Vol. 36, No. 1
 * Kunihito Hoki, Tomoyuki Kaneko (**2014**). //[|Large-Scale Optimization for Evaluation Functions with Minimax Search]//. [|JAIR Vol. 49], [|pdf] » Automated Tuning, Shogi

=External Links=
 * [|Kunihito Hoki's ICGA Tournaments]
 * [|保木 邦仁 / Kunihito Hoki – TEDxKids@Chiyoda 2012]

=References= =What links here?= include page="Kunihito Hoki" component="backlinks" limit="40"
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