EAGER: Developing a Mathematical Framework to Enable Bi-Directional Interactions of Humans with Smart Engineered Systems Using Relational Elements

EAGER：开发一个数学框架，利用关系元素实现人类与智能工程系统的双向交互

• 批准号: 1548517
• 负责人: Burcin Becerik-Gerber
• 金额: $ 25万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1548517&HistoricalAwards=false
• 关键词: EAGER; Developing; Mathematical; Framework; Enable

Buildings consume a staggering 38 percent of our nation's total energy use. Existing automation approaches to address this problem focus either on buildings, allowing them to better sense and respond to the behavior of their occupants, or focus on occupants, seeking to educate them on making more efficient energy choices. In contrast, this EArly-concept Grant for Exploratory Research (EAGER) project considers ways to enhance the interaction between buildings and occupants. The research team hypothesizes that user-building interactions will be most effective when building users establish a relationship of trust with building automation. By developing mathematical models and theory that amplify user capabilities through relational features, users are empowered to improve individual performance as well as building performance, while also improving societal well-being. To do so, the work draws on theories from the behavioral sciences to mathematically model when and how a building should interact with a user and how these interactions should be framed. The results will change the way we perceive and experience today's built environments, leading what could become the creation of unprecedented built environments that are attentive and have an identity. The project will enhance infrastructure for research and education by making the models and data available via a free research license, incorporating research findings into the engineering curriculum, disseminating research findings via publications, and national and international presentations. The modeling framework for user-virtual human agent interactions is the key contribution to smart engineered systems modeling and design and occurs at the intersection of engineering, the behavioral sciences and computational modeling. If successful, the mathematical framework will be used to design smart buildings that have two-way interactions with people. The research objectives contribute to the ultimate goal of enabling cyber-physical systems to interact and collaborate with humans. This project integrates experimental data into the mathematical models, testing the inclusion of relational elements embedded in the personification of a building. The models will predict which response is the most suitable for a building-user interaction. This model will also be informed and constrained by existing theoretical work on persuasion. The model will account for various contextual, temporal and personal factors as well as the changes in user response due to continuous interactions with the building. The multiple-step modeling methodology incorporates a combination of machine learning techniques, mathematical projections for the classification problem, and statistical models such as Markov model, and autoregressive moving average models. In particular, the contributions are twofold: (1) modeling user-building interactions using virtual human agents personifying buildings; and (2) performing fundamental research on how theories of human interpersonal trust and influence can inform the design of automation. The research will contribute to the fundamental understanding of human-machine teamwork, including elucidating theories of why and how people build connections with automated systems and advance our general understanding of how automation exhibiting relational features can facilitate behavior change in the population served by those systems.

建筑物消耗了我们国家总能源消耗的38%。解决这一问题的现有自动化方法要么集中在建筑物上，使它们能够更好地感知和响应居住者的行为，要么集中在居住者身上，试图教育他们做出更有效的能源选择。相比之下，EARLY概念探索性研究资助（EAGER）项目考虑如何增强建筑物和居住者之间的互动。研究团队假设，当建筑用户与建筑自动化建立信任关系时，用户与建筑的交互将是最有效的。通过开发数学模型和理论，通过关系特征放大用户的能力，用户有能力提高个人表现以及建立表现，同时也提高社会福祉。为此，这项工作借鉴了行为科学的理论，对建筑物何时以及如何与用户互动以及如何构建这些互动进行了数学建模。其结果将改变我们感知和体验当今建筑环境的方式，从而创造出前所未有的建筑环境，这些建筑环境既专注又具有身份。该项目将通过免费研究许可证提供模型和数据，将研究成果纳入工程课程，通过出版物以及国家和国际演示传播研究成果，从而加强研究和教育的基础设施。用户-虚拟人代理交互的建模框架是智能工程系统建模和设计的关键贡献，并且发生在工程、行为科学和计算建模的交叉点。如果成功，数学框架将用于设计与人双向互动的智能建筑。研究目标有助于实现网络物理系统与人类互动和协作的最终目标。 该项目将实验数据集成到数学模型中，测试嵌入在建筑物拟人化中的关系元素的包含性。这些模型将预测哪种响应最适合建筑物-用户交互。这个模型也将受到现有说服理论工作的影响和约束。该模型将考虑各种上下文，时间和个人因素，以及由于与建筑物的持续互动而引起的用户响应的变化。多步建模方法结合了机器学习技术、分类问题的数学预测以及诸如马尔可夫模型和自回归移动平均模型的统计模型。特别是，贡献是双重的：（1）使用拟人化建筑物的虚拟人代理建模用户建筑交互;（2）对人类人际信任和影响力的理论如何为自动化设计提供信息进行基础研究。这项研究将有助于对人机团队合作的基本理解，包括阐明人们为什么以及如何与自动化系统建立联系的理论，并推进我们对自动化如何表现出关系特征可以促进这些系统所服务的人群的行为变化的一般理解。