Generic Tasks of Scientific Discovery

在模拟科学发现方面。 在过去的几年里，这个小组已经开发了几个计算机程序，自动化生物学，化学，物理学和一般实验科学的科学发现的重要方面。 他们通过研究科学文章等主要来源，与广泛的科学家交谈，甚至在一些国家进行“实地工作”，确定了有希望的发现任务。 科学 自动化方法包括启发式的概念和技术 搜索，算法和优化， 和 初级数学和统计学。 各个领域的具体结果支持了这样一个假设，即今天很大一部分科学推理可以自动化。 然而， 假设大量的科学推理由非常具体的通用任务组成，但是-在其计算本质上-对多门科学来说是共同的。 一般科学任务的概念是一种新的方式来看待生物学，计算化学等计算。 本研究探讨了“通用科学任务”的概念，通过调查它是否会导致实际的结果（科学家的强大发现工具），以及如何提供一个更系统的理解科学推理。

In modeling scientific discovery. Over the last several years, this group has developed several computer programs that automate important aspects of scientific discovery in biology, chemistry, physics, and also general experimental science. They have identified promising discovery tasks by studying primary sources such as scientific articles, talking with a broad array of scientists, and even doing "field work" in some science. Automation methods have included the concepts and techniques of heuristic search, of algorithms and optimization, and a elementary mathematics and statistics. Concrete results in various fields back up the hypothesis that a significant fraction of scientific inference can be automated today. There is, however, the hypothesis that mush of scientific inference consists of generic tasks that are quite specific, but that - in their computational essence - are common to multiple sciences. The concept of generic scientific task is a new way to view computing in biology, computational chemistry, and so on. This research explore the concept of "generic scientific task" by investigating whether it leads to practical results (powerful discovery tools for scientists), and how this can provide a more systematic understanding os scientific inference.