GVGAI Games

该数据集包含了20款游戏，用于评估不同变体的rhNEAT算法的性能。这些游戏在难度和类型上各不相同，为研究提供了丰富的环境。每款游戏在5个难度级别下各运行100次，使得该数据集能够在GVGAI框架内对不同算法及配置进行全面的比较分析。这一规模庞大的数据集，涵盖了多次重复实验，旨在对视频游戏中的算法性能进行深入评估。

This dataset comprises 20 video games, designed to evaluate the performance of various variants of the rhNEAT algorithm. These games differ in terms of difficulty level and game genre, offering a diverse and robust experimental environment for academic research. Each game is executed 100 times across 5 distinct difficulty tiers, enabling comprehensive comparative analyses of different algorithms and their configurations within the GVGAI framework. This large-scale dataset, which includes numerous replicated experimental trials, is developed to conduct in-depth assessments of algorithm performance in video game settings.