Building Temperature Control Problem
收藏arXiv2025-09-30 收录
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https://github.com/lukearcus/ScenarioAbstraction
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资源简介：
该数据集旨在为一个两室建筑优化满足温度控制规格的概率模型。目标是在避免临界温度范围的同时，保持温度在22至23摄氏度之间。在假设B的条件下，该数据集被划分为1600个区域，形成了一个具有较少转换关系的较小交互式马尔可夫决策过程（iMDP）。任务是在不确定动态下进行温度调节。
This dataset is developed for optimizing probabilistic models that meet temperature control specifications for a two-bedroom building. The objective is to maintain the indoor temperature within the range of 22 to 23 °C while avoiding critical temperature ranges. Under Assumption B, this dataset is partitioned into 1600 regions, forming a smaller interactive Markov Decision Process (iMDP) with fewer transition relationships. The task is to perform temperature regulation under uncertain dynamics.
