In this paper, we derive and implement a probabilistic programming idiom for the problem of acquiring new knowledge about an environment. The idiom is implemented utilizing a modern probabilistic programming language. We demonstrate the utility of this idiom by implementing an algorithm for the specific problem of active mapping and robot exploration. Finally, we evaluate the functionality of the implementation through an extensive simulation study utilizing the HouseExpo dataset.

翻译：在本文中,我们为获得关于环境的新知识的问题制定并实施一种概率性编程标准。该标准使用一种现代概率性编程语言来实施。我们通过对主动绘图和机器人探索的具体问题实施算法来证明这一标准的作用。最后,我们通过利用HouseExpo数据集进行广泛的模拟研究来评估执行的功能。