CRII: SHF: Supporting Domain-Specific Inquiry with Rule-Based Modeling

编写生态、经济模型、社会动态、政府程序和生物监管等过程的计算机模拟，可以让新手和在世的专家更好地理解这些系统。基于规则的建模允许新手程序员指定和运行这些模拟，而不需要接受概率理论或传统编程语言的培训。该工作扩展了一种基于规则的建模语言，以支持语言的自我指导学习和特定于领域的模型查询。从长远来看，这项工作将使不同领域的专家之间能够进行交叉交流，并将扩大对跨STEM学科适用的系统思维技能的参与。基于规则的底层语言Ceptre基于线性逻辑的片段，能够对程序进行组合推理。拟议的工作需要为Ceptre开发一个结构编辑器，旨在支持以下关键原则：可发现性、支持新用户以自我指导的方式学习语言以及通过仅在有意义的编辑状态之间映射的编辑界面实现逐句更正或防止语法错误。该项目的这一部分将经过严格验证，以证明编辑界面在基本语文方面是健全和完整的。该项目的领域特定查询部分将通过开发一种语言和算法来实现，以支持对模拟状态的查询和过滤器、关于程序跟踪的“为什么”问题、对跟踪集的统计分析以及其他理解模拟紧急行为的方法。这些工具将通过对领域专家和编程新手群体的用户研究进行评估。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Writing computer simulations of processes such as ecologies, economic models, social dynamics, government procedures, and biological regulation, can lead to greater understanding of these systems for novices and experts alive. Rule-based modeling allows novice programmers to specify and run these simulations without training in probability theory or traditional programming languages. The proposed work extends a rule-based modeling language to support self-directed learning of the language and domain-specific inquiry about the models. In the long term, this work will enable cross-communication between experts in different domains and will broaden participation in systems thinking skills applicable across STEM disciplines.The underlying rule-based language, Ceptre, is based on a fragment of linear logic, enabling compositional reasoning about programs. The proposed work entails developing a structure editor for Ceptre designed to support the key principles of discoverability, supporting new users to learn the language in a self-directed manner, and correctness-by-construction, or the prevention of syntax errors through an editing interface that maps between only meaningful edit states. This part of the project will be rigorously validated with formal proofs of soundness and completeness of the editing interface with respect to the underlying language. The domain-specific inquiry component of the project will be accomplished by developing a language and algorithms to support queries and filters on simulation states, "Why" questions about program traces, statistical analysis on sets of traces, and other means of understanding the emergent behavior of simulations. These tools will be evaluated through user studies on populations of domain experts and programming novices.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.