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

CRII：SHF：通过基于规则的建模支持特定领域的查询

• 批准号: 1755922
• 负责人: Christopher Martens
• 金额: $ 16.11万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-03-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1755922&HistoricalAwards=false
• 关键词: CRII; SHF; Supporting; Domain; Specific

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.

编写生态学、经济模型、社会动力学、政府程序和生物监管等过程的计算机模拟，可以让新手和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，而无需接受概率论或传统编程语言的培训。所提出的工作扩展了基于规则的建模语言，以支持自主学习的语言和特定领域的查询模型。从长远来看，这项工作将使不同领域的专家之间的交叉交流，并将扩大参与系统思维技能适用于跨STEM学科。底层的基于规则的语言，Ceptre，是基于线性逻辑的片段，使组合推理的程序。拟议的工作需要为Ceptre开发一个结构编辑器，旨在支持可扩展性的关键原则，支持新用户以自我指导的方式学习语言，以及通过构造纠正或通过仅在有意义的编辑状态之间映射的编辑界面来防止语法错误。项目的这一部分将通过正式的证据进行严格的验证，以证明编辑界面相对于底层语言的可靠性和完整性。该项目的特定领域查询组件将通过开发一种语言和算法来完成，以支持对模拟状态的查询和过滤，关于程序跟踪的“为什么”问题，对跟踪集的统计分析，以及理解模拟的紧急行为的其他方法。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，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估。

项目成果

The Ceptre Editor: A Structure Editor for Rule-Based System Simulation

Ceptre 编辑器：用于基于规则的系统仿真的结构编辑器

• DOI: 10.1109/vlhcc.2019.8818687
• 发表时间: 2019
• 期刊: 2019 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC
• 作者: Card, Alexander;Martens, Chris
• 通讯作者: Martens, Chris