Monte-Carlo methods are the basis for solving many computational problems using repeated random sampling in scenarios that may have a deterministic but very complex solution from a computational point of view. In recent years, researchers are using the same idea to solve many problems through the so-called Monte-Carlo Tree Search family of algorithms, which provide the possibility of storing and reusing previously calculated results to improve precision in the calculation of future outcomes. However, developers and researchers working in this area tend to have to carry out software developments from scratch to use their designs or improve designs previously created by other researchers. This makes it difficult to see improvements in current algorithms as it takes a lot of hard work. This work presents JGraphs, a toolset implemented in the Java programming language that will allow researchers to avoid having to reinvent the wheel when working with Monte-Carlo Tree Search. In addition, it will allow testing experiments carried out by others in a simple way, reusing previous knowledge.

中文翻译：

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JGraphs：使用基于蒙特卡洛树搜索的算法的工具集

Monte-Carlo 方法是在从计算的角度来看可能具有确定性但非常复杂的解决方案的场景中使用重复随机抽样解决许多计算问题的基础。近年来，研究人员正在使用相同的想法通过所谓的蒙特卡洛树搜索系列算法解决许多问题，这些算法提供了存储和重用先前计算结果的可能性，以提高计算未来结果的精度。然而，在这一领域工作的开发人员和研究人员往往不得不从头开始进行软件开发，以使用他们的设计或改进其他研究人员以前创建的设计。这使得很难看到当前算法的改进，因为这需要大量的努力。这项工作介绍了 JGraphs，一个用 Java 编程语言实现的工具集，使研究人员在使用 Monte-Carlo 树搜索时避免重新发明轮子。此外，它将允许其他人以简单的方式进行测试实验，重用以前的知识。