25,161
edits
Changes
no edit summary
a [[Supervised Learning|supervised]] [[Automated Tuning|tuning method]] based on [[Automated Tuning#MoveAdaption|move adaptation]],
devised and introduced by [[Kunihito Hoki]] and [[Tomoyuki Kaneko]] <ref>[[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://pdfs.semanticscholar.org/eb9c/173576577acbb8800bf96aba452d77f1dc19.pdf pdf]</ref>.
A MMTO predecessor, the initial '''Bonanza-Method''' was used in Hoki's [[Shogi]] engine [[BonanazaBonanza]] in 2006, winning the [[WCSC16]] <ref>[[Kunihito Hoki]] ('''2006'''). ''Optimal control of minimax search result to learn positional evaluation''. [[Conferences#GPW|11th Game Programming Workshop]] (Japanese)</ref>.
The further improved MMTO version of Bonanaza won the [[WCSC23]] in 2013 <ref>[[Takenobu Takizawa]], [[Takeshi Ito]], [[Takuya Hiraoka]], [[Kunihito Hoki]] ('''2015'''). ''[https://link.springer.com/referenceworkentry/10.1007/978-3-319-08234-9_22-1 Contemporary Computer Shogi]''. [https://link.springer.com/referencework/10.1007/978-3-319-08234-9 Encyclopedia of Computer Graphics and Games]</ref>.
