Bonanza

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Bonanza team performs distributed tree search [1]

Bonanza, (Bonanza Feliz)
an XBoard compliant Category: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, dubbed KPP or KKP, 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].

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