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CLOP: Confident Local Optimization for Noisy Black-Box Parameter Tuning by Rémi Coulom Abstract Artificial intelligence in games often leads to the problem of parameter tuning. Some heuristics may have coefficients, and they should be tuned to maximize the win rate of the program. A possible approach is to build local quadratic models of the win rate as a function of program parameters. Many local
Welcome to my home page. I have been working at Kayufu since 2014. My e-mail address is R e m i . Coulom at gmail dot com. On this page, you'll find some of my software and papers. I also post news on Facebook, and Twitter. In the past, I was Associate Professor of Computer Science at the Lille 3 University, and a member of the SequeL research group. I am hosting the Game AI Forum, goratings.org,
If you have any problem buying or using Crazy Stone, please contact Unbalance, not me. History 2016-03-21: Crazy Stone took the third place of the UEC Cup. It is considerably stronger thanks to deep learning. It reached 7d on KGS, and entered the KGS top 100! 2015-03-21: Crazy Stone won the UEC Cup, and lost a 3-stone game against Cho Chikun in the Densei-sen. 2014-03-24: Recently, Crazy Stone est
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