CPS EAGER: Intelligent Agent Incident Command System Augmentation

智能城市是复杂的网络物理系统，庞大的人口增加了额外的复杂性。仪表和建模是智能城市的组成部分。然而，不管仪器的普遍性和模型的精确度，最终，人类和人类团队将对城市范围内的运营和管理做出决定，特别是在危机中。我们认为，现代指挥和控制系统的层级性质可能会造成虚拟盲点，其中机会或危险可能对层级不可见，因为必要的信息在层级中的抽象级别之间移动时被遮蔽。该项目将涉及与危机管理专家和研究人员合作，开发旨在将决策者的认知负荷降至最低的智能代理，利用报告和传感器数据中的语义关系来对其他看不见的事件提供建议，并对基层资产的行动进行排序，以改进因果关系模型，以更好地反映危机和/或事件管理期间的持续发展。该项目解决了以下技术差距(S)，因为它从研究发现转化为商业应用-a)在代理可以支持和增强人类决策而不增加人类认知工作量的情况下，展示信息呈现的有效性和透明度；b)将最先进的语义数据和信息集成的基础研究转移到复杂的灾难场景；c)开发模型一致性维护工具，用于自动更新各种灾难和/或紧急情况的因果模型。此外，参与该项目的人员，例如研究生，将通过开发的模型的设计、开发和测试获得创新经验。该项目将探索研究成果在其他应用领域的工具的可转换性，如辅助救援员培训、AFRL灾害响应系统涟漪和克拉克县紧急事务管理署。该项目还将与发现实验室的高中生和本科生进行外展工作，帮助他们度过边缘的暑假/边缘之年计划(SATE/YATE)。

Smart Cities are complex cyber-physical systems with large human populations adding additional complexity. Instrumentation and modeling are components of a smart city. Regardless, however, of the ubiquity of instrumentation and precision of models, in the end, humans and human teams will make decisions about citywide operations and management, especially in crisis. We contend that the hierarchical nature of contemporary command and control systems can create virtual blind spots in which opportunities or dangers may be invisible to the hierarchy because the necessary information is obscured as it moves between levels of abstraction in the hierarchy. This project will involve teaming with crisis management experts and researchers to develop intelligent agents designed to minimize cognitive load on decision makers, exploit semantic relationships in reports and sensor data to advise of otherwise invisible occurrences, and sequence the actions of ground-level assets to refine causal relationship models to better reflect ongoing developments during crisis and/or event management. This project addresses the following technology gap(s) as it translates from research discovery toward commercial application - a) demonstration of the effectiveness of information presentation and transparency in situations where agents can support and enhance human decision-making without increasing the cognitive workload of the human; b) transfer state-of-the-art foundational research in semantic data and information integration to the complex disaster scenario; c) development of model consistency maintenance tools for automatic update of causal models of various disaster and/or emergency situations. In addition, personnel involved in this project, e.g., graduate students, will receive innovation experiences through the design, development and testing of the model developed.This project will explore transferability of the research results into tools in other application areas such as Pararescuer training, AFRL disaster response system RIPPLE, and Clark County Emergency Management Agency. This project will also have outreach efforts with mentoring high school and undergraduate students at Discovery Lab, Tec^Edge through the Summer at the Edge/Year at the Edge Programs (SATE/YATE).