EAGER: Theoretical Foundation for the Use of Approximations and Heuristics in Systems Engineering and Design

在实践中，工程师经常依赖于算法和近似来高效和有效地达到良好的系统设计。 启发式是体现工程经验的经验法则。 如果使用得当，它们可以节省工程时间和精力，而不会牺牲系统的质量。 然而，对近似法和近似法的使用知之甚少。 EARLY概念探索性研究（EAGER）项目将使人们能够对设计理论和相关流程进行基本的理解和开发，指导研究人员和从业人员推进和使用此类理论，并最终为设计科学提供正式的基础。这项研究将结合联合收割机的数学基础，如概率论和决策理论，与学生和有经验的工程师的经验观察，以开发解释模型，用于计算和近似。 该研究将从各种不同的方法中形式化设计方法，并建议如何以及何时在设计实践中最好地使用方法。此外，它将导致关于如何更好地教授设计的新见解，通过明确识别设计知识的启发性，并通过指导学生通过底层基础的情境化和终身学习来不断更新他们的知识。系统工程和设计目前缺乏强大的理论基础，特别是，社区一直在努力弥合当前实践与作为系统工程和设计基础的规范性、公理化、数学理论之间的差距。 为了填补这方面的知识空白，本研究的目的是提高科学的理解，在系统工程和设计中使用的近似和几何学。一个规范的理论将推导出使用的近似值和显式会计执行设计师的行动所需的资源的价值，从冯诺依曼-摩根斯坦公理的决策理论。发现的启发式将被归类并通过表征其价值或有效性进行分析。“在心理学中研究的设计心理学和认知心理学之间的关系将被考虑，弥合描述性和规定性理论之间的差距，确定两者之间的差距，并得出假设，在规范理论和当前实践之间的差距似乎很大的情况下，设计实践的改进。这项研究将有助于实现设计原理和相关过程的基本理解和发展，并将指导研究人员和从业人员在进步和使用这样的原理，并最终提供正式的基础，设计科学。

In practice, engineers often rely on heuristics and approximations to arrive at good system designs efficiently and effectively. Heuristics are rules of thumb that embody engineering experience. When used appropriately, they save engineering time and effort without sacrificing the quality of the system being engineered. However, the use of heuristics and approximations is poorly understood. This EArly-concept Grant for Exploratory Research (EAGER) project will enable a fundamental understanding and development of design heuristics and associated processes, guiding researchers and practitioners in advancements and use of such heuristics, and ultimately, providing a formalized foundation to design science. The research will combine mathematical foundations, such as probability theory and decision theory, with empirical observations of students and experienced engineers to develop explanatory models for the use of heuristics and approximations. The research will make strides in formalizing design heuristics from various disparate approaches, and recommend how and when heuristics are best used in design practice. In addition, it will lead to new insights regarding how to teach design better by clearly identifying the heuristic nature of design knowledge, and by coaching students to continually update their heuristics through the contextualization of the underlying foundations and through life-long learning.Systems engineering and design currently lack a strong theoretical foundation, and, in particular, the community has struggled to bridge the gap between current practice and the normative, axiomatic, mathematical theories that underlie systems engineering and design. To fill this gap in knowledge, the objective of this research is to enhance the scientific understanding of the use of approximations and heuristics in systems engineering and design. A normative theory will be derived for the use of approximations and heuristics by explicitly accounting for the value of the resources required to execute designer actions, starting from the von Neumann-Morgenstern axioms of decision theory. Heuristics found will be cataloged and analyzed by characterizing their value or 'validity.' The relationship between design heuristics and cognitive heuristics as studied in psychology will be considered, bridging the gap between descriptive and prescriptive theories, identifying gaps between the two, and deriving hypotheses regarding the improvement of design practice in situations in which the gap between normative theory and current practice appears to be large. This research will assist in enabling a fundamental understanding and development of design heuristics and associated processes, and will guide researchers and practitioners in advancements and use of such heuristics, and ultimately, provide formalized foundations to design science.