RI: Small: Automated Planning of Experiments for Design Optimization

许多工程和科学项目需要计划实验活动，以优化目标。这种规划涉及对各项活动之间资源有限的制约因素沿着这些活动可能提供的潜在信息的效用进行联合推理。不幸的是，对于许多现实世界的规划问题，与丰富的潜在活动之间的结构，从经典的实验设计的工具是不直接适用，由于其简化的假设和可扩展性差。该项目旨在通过开发新的算法来改变实验规划的实践，这些算法可以解释在广泛领域中表现出的复杂性。该项目涉及三个关键活动。首先，实验设计描述语言（EDDL）正在创建正式建模复杂的现实世界的实验领域。其次，正在开发新的规划算法，以有效地计算高质量的解决方案，在EDDL中表示的问题。第三，与生物工程师的合作是评估和改进工具的可用性，并根据真实的和模拟的生物工程数据产生基准问题。语言和基准的创建将有助于促进算法的比较，为更广泛的研究社区的持续进步，该项目的更广泛的影响是，以促进实验规划在广泛的实验领域，目前还没有可用的计算工具。目前，在这些领域，规划主要是临时性的，往往没有计算机支持。我们的研究通过帮助工程师和科学家从有限的实验资源中获得最大价值，具有广泛的经济影响潜力。该项目还促进了计算机科学和生物工程领域的高中、本科和研究生教育，重点是招收女生。学生将获得跨学科和研究实验室工作的独特经验。

Many engineering and scientific projects require planning experimental activities in order to optimize an objective. Such planning involves jointly reasoning about both the budget-limited resource constraints among activities along with the utility of potential information that they may provide. Unfortunately, for many real-world planning problems, with rich structure among potential activities, tools from classic experimental design are not directly applicable due to their simplifying assumptions and poor scalability. This project aims to transform the practice of experimental planning by developing new algorithms that account for the complexities exhibited in a wide range of domains.The project involves three key activities. First, the experimental design description language (EDDL) is being created for formally modeling complex real-world experimental domains. Second, novel planning algorithms are being developed for efficiently computing high-quality solutions to problems expressed in EDDL. Third, work with bioengineers is assessing and improving the usability of the tools and producing benchmark problems based on real and simulated bioengineering data. The creation of the language and benchmarks will help facilitate algorithm comparisons for continued progress by the wider research community.The broader impact of the project is to facilitate experiment planning in a wide range of experimental domains for which there are currently no available computational tools. Currently, in such domains, planning is largely ad-hoc and often done without computer support. Our research has broad economic impact potential by helping engineers and scientists to get the most value out of limited experimental resources. The project also advances high school, undergraduate, and graduate education in the areas of computer science and bio-engineering, with an emphasis on recruiting female students. The students will get the unique experience of working across disciplines and research labs.