mario_rl:强化学习应用于马里奥
这是同时进行所有32个级别的培训的10秒快照。
当前任务
创建一个新的GameRunner类以运行多个级别并将结果同步到一个主模型中。 例如，不是在一个级别上进行训练，而是在所有32个级别上进行训练（并行！），然后更新模型。
其他任务
替换整洁的python库（可能是为了娱乐而创建一个自定义库）
构建自定义检查点系统（或了解如何解决整洁的Python索引错误）
添加有关如何生成“良好”配置文件的信息-时间戳为1566017738的配置是“最佳”配置之一
绘制随机超参数作为人口规模的函数。 看看前20个左右的人口是否少。 将此添加到自述文件。
使用自述文件将生成的数据移至外部存储，其中每个数据文件夹分别是什么以及是否已在其上运行实验。 （此存储库中未包括的数据为许多GB，但应保留其中一些数据以作进一步研究。）
完成主自述文件:)
添加有关使用一些数据和图形进行超参数搜索的文档。
有
文件下载
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本站所有资源不代表本站的观点或立场，基于网友分享，根据中国法律《信息网络传播权保护条例》第二十二条之规定，若资源存在侵权或相关问题请联系本站客服人员，zhiweidada#qq.com，请把#换成@，本站将给予最大的支持与配合，做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明