Bonanza

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[ Bonanza team performs distributed tree search [1] Bonanza, (Bonanza Feliz)

an XBoard compliant open source Shogi engine developed by primary author Kunihito Hoki, started in 2004, at times supported by Takuya Obata, Takuya Sugiyama, and Takeshi Ito [2]. Bonanza is top contender at Computer Olympiads and World Computer Shogi Championships and so far two times champion, winning the WCSC16 in 2006, and the WCSC23 in 2013 [3].

Description

Bonanza is written in C and utilizes 9x9 Bitboards in form of three 32-bit unsigned integers. It is a fractional ply alpha-beta engine performing a principal variation search with transposition table, null move pruning, recursive iterative-deepening for PV-nodes, various extensions, reductions, and futility pruning. Bonanza pioneered in large-scale machine learning of static evaluation functions, a supervised tuning method based on move adaptation, dubbed the Bonanza Method which evolved to Minimax Tree Optimization (MMTO). Bonanza utilizes and tuned piece-square tables indexed by king location and further two-piece locations and side to move (turn), dubbed KPP, KKP or KPPT, which was used in many other Shogi programs [4], and has influenced the design of NNUE [5].

Beside a parallel tree search, Bonanza is able to apply parallelization by the so called Consensus method [6], a kind of triple-brain approach where multiple, slightly modified instances of the same engine vote for the best move [7] [8].

Publications

Forum Posts

Shogi Engine

Misc

References

  1. Photo of the main cast of Bonanza. From left - Dan Blocker (Hoss), Michael Landon (Little Joe), Lorne Greene (Ben), Pernell Roberts (Adam), September 20, 1959, Author: NBC Television. Category:Bonanza (TV series) - Wikimedia Commons
  2. WCSC20 Participant List by Nobu, SHOGI-L, February 02, 2010
  3. Takenobu Takizawa, Takeshi Ito, Takuya Hiraoka, Kunihito Hoki (2015). Contemporary Computer Shogi. Encyclopedia of Computer Graphics and Games
  4. The 25th World Computer Shogi Championships by Reijer Grimbergen on behalf of Takenobu Takizawa, SHOGI-L, February 11, 2015
  5. 機械学習エンジニアのための将棋AI開発入門その1 Introduction to Shogi AI development for machine learning engineers Part 1, May 03, 2020 (Japanese)
  6. Bonanzaの特徴は、 Characteristics of Bonanza - wcsc23 2013
  7. Takuya Obata, Takuya Sugiyama, Kunihito Hoki, Takeshi Ito (2010). Consultation Algorithm for Computer Shogi: Move Decisions by Majority. CG 2010
  8. Kunihito Hoki, Seiya Omori, Takeshi Ito (2014). Analysis of Performance of Consultation Methods in Computer Chess. Journal of Information Science and Engineering, Vol. 30, pdf
  9. MMTO for evaluation learning by Jon Dart, CCC, January 25, 2015

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