The Capabilities and Limitations of Atomated Discovery

归纳推理中使用的模型源于讨论科学方法的科学哲学家使用的模型。在学习理论的早期工作中，目标是对正在考虑的现象做出解释。然而，科学家很少直接为完整解释的宏伟目标而工作，而是寻求更温和的目标，即找到观察数据的特征和事实。 同样，这个项目追求对归纳推理中使用的传统模型进行几次修改，以便研究追求更适度的科学目标。 这项研究与当代科学特别相关，因为自动数据生成技术产生了足够多的数据，足以压倒人类的分析能力。我们工作的目标是精确地阐明自动数据分析算法可以和不能完成的事情。

The models used in inductive inference have their roots in the models used by the philosophers of science who were discussing the scientific method. The goal there, and in prior work in learning theory, was to come up with an explanation of the phenomenon under consideration. However, scientists rarely work directly for the grand goal of a complete explanation, seeking rather the more modest goal of finding features and facts about the observed data. In like manner, this project pursues several modifications to the traditional models used in inductive inference so as to study the pursuit of more modest scientific goals. This study is particularly relevant to contemporary science as automated data generation techniques produce sufficient volumes of data to overwhelm the analysis abilities of humans. The goal of our work is to illuminate precisely what can and cannot be accomplished by automatic data analysis algorithms.