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a [[Chess Engine Communication Protocol]] compatible chess engine by [[Arkadiusz Paterek]], originated as a part of his masters thesis. In [https://en.wikipedia.org/wiki/Korean_language Korean ] [https://en.wikipedia.org/wiki/Gosu its name ] means "expert"or master.

In Arkadiusz Paterek's paper ''Modeling of an evaluation function in games'' <ref>[[Arkadiusz Paterek]] ('''2004'''). ''Modelowanie funkcji oceniającej w grach''. [[University of Warsaw]], [https://www.mimuw.edu.pl/~paterek/mfog.ps.gz zipped ps] (Polish, Modeling of an evaluation function in games)</ref>, referring his thesis ''Modeling of an evaluation function in chess'', the [[Evaluation|evaluation]] is mentioned using a [[Neural Networks#Perceptron|single-layer perceptron]] design inspired by [[Michael Buro|Michael Buro's]] [[Michael Buro#GLEM|general linear evaluation model]] (GLEM) <ref>[[Michael Buro]] ('''1998'''). ''[http://link.springer.com/chapter/10.1007/3-540-48957-6_8 From Simple Features to Sophisticated Evaluation Functions]''. [[CG 1998]], [https://skatgame.net/mburo/ps/glem.pdf pdf]</ref> in the domain of [[Othello]]. Gusu Gosu performs [[Automated Tuning#LogisticRegression|logistic regression]] to optimize weights of corresponding features aka minimize the [https://en.wikipedia.org/wiki/Mean_squared_error mean squared error] [https://en.wikipedia.org/wiki/Loss_function loss function] by [https://en.wikipedia.org/wiki/Gradient_descent gradient descent] over a set of 6.2 million quiet positions from master games. For each position, using it squares the difference of an [[Oracle|oracle]] score from the outcome of the game, of 0.999 for a win, 0.5 for a draw, and 0.0013 for a loss versus , and the [https://en.wikipedia.org/wiki/Dot_product dot product] of a the weight and [https://en.wikipedia.org/wiki/Feature_(machine_learning) feature vector] as [[Score|score]] of the position, squashed by a [https://en.wikipedia.org/wiki/Logistic_function logistic function] into a 0.0 to 1.0 range of a [[Pawn Advantage, Win Percentage, and Elo|winning probability]]. To speed up matters after [[Automated Tuning|tuning]], an [[Evaluation Hash Table|evaluation cache]] is used along with [[Lazy Evaluation|lazy evaluation]], which performed well in Gosu's [[MTD(f)]] framework.

* [http://www.open-aurec.com/wbforum/viewtopic.php?f=2&t=127 Gosu does not find the mate in 1...] by [[Dr. Axel Schumacher]], [[Computer Chess Forums|Winboard Forum]], October 03, 2004» [[Checkmate]]

* [http://www.talkchess.com/forum3/viewtopic.php?f=2&t=25286 Gosu 0.16 v Thor's Hammer 2.28 (queen sac)] by [[Graham Banks]], [[CCC]], December 06, 2008» [[Thor's Hammer]]