论文标题
国际象棋引擎优化的贝叶斯统计方法
Bayesian statistics approach to chess engines optimization
论文作者
论文摘要
我们使用贝叶斯统计方法开发了一种新方法来进行随机优化。更确切地说，我们优化了国际象棋发动机的参数，因为这些数据可用于我们，但是该方法应适用于我们想要优化某些没有分析形式的某些增益/损耗函数的情况，因此不能直接测量，仅通过比较两个参数集进行测量。我们还通过实验将新方法与著名的SPSA方法进行比较。
We develop a new method for stochastic optimization using the Bayesian statistics approach. More precisely, we optimize parameters of chess engines as those data are available to us, but the method should apply to all situations where we want to optimize a certain gain/loss function which has no analytical form and thus cannot be measured directly but only by comparison of two parameter sets. We also experimentally compare the new method with the famous SPSA method.
