Collaborative Research: SOTERIA: Satisfaction and Risk-aware Dynamic Resource Orchestration in Public Safety Systems

公共安全系统(PSS)处理受害者、第一反应人员和紧急控制中心(ECC)，这些中心在灾难期间和灾后协调救援任务。目前，对于人类如何在灾难发生后做出利用个人和共享资源的决定的理解有限；而且，现有的模型大多是定性的。灾难场景中有限的信息可获得性和PSS中的资源不确定性构成了两大挑战：(1)考虑到受害者关于动态资源编排的风险意识(自主)决策特征，如何获得受害者的满意度？以及(2)如何设计一个有弹性的灾难应对系统，以激励受害者参与众包？创新的Soteria项目通过提出一种新的行为决策模型来应对这些挑战，该模型捕捉了人类在资源可用性不确定的风险下的决策特征。它在博弈论中引入了一个新的领域，称为满意博弈，旨在满足受害者的最低服务要求，而不是最大化他们的总体满意度，解决了PSS中的资源管理问题。还提出了一种新颖的生物启发灾难响应网络(DRN)，该网络模拟生物网络固有的健壮性，支持受害者参与可靠的众包，同时基于新发明的贝叶斯前景理论来评估收集到的信息的真实性和质量。所提出的方法和系统将使用真实世界的现场数据进行评估。Soteria项目将在PSS中创建新的分布式控制、优化和可扩展的资源管理技术。其创新之处在于，综合考虑了人类行为和共享资源的公地悲剧现象，有效地管理资源，从而提高了受害者的满意度，而不是效用最大化。为了处理有关资源可获得性的不完全信息，所提出的强化学习技术将增强受害者的实时决策能力。该项目的研究成果通过设计强大的情景感知灾难响应网络并推进展望理论、公地悲剧和满意游戏的最新研究，在支持ECC活动以及在灾难发生和灾难发生后拯救人们的生命和基础设施方面具有巨大的潜力。该项目将培训本科生和研究生，研究成果将通过项目网站和高质量出版物传播。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。

Public Safety Systems (PSS) deal with victims, first responders, and emergency control centers (ECCs) that coordinate the rescue missions during and aftermath of a disaster. Currently, there is limited understanding of how humans make decisions to utilize personal and shared resources in the wake of disasters; moreover, the existing models are mostly qualitative. Limited information availability in disaster scenarios and resource uncertainty in PSSs pose two major challenges: (1) how to achieve the victims’ satisfaction accounting for their risk-aware (autonomous) decision-making characteristics about dynamic resource orchestration? and (2) how to design a resilient disaster response system incentivizing the victims’ participation in crowdsourcing? The innovative SOTERIA project addresses these challenges by proposing a novel behavioral decision-making model that captures humans’ decision-making characteristics under risk, stemming from uncertain availability of resources. It introduces a new field in game theory, called Satisfaction Games that aims to satisfy the victims’ minimum service requirements rather than maximizing their overall satisfaction, addressing the resource management problems in PSSs. A novel bio-inspired Disaster Response Network (DRN) is also proposed that mimics the inherent robustness of biological networks of living organisms, to support the victims’ participation in reliable crowdsourcing, while the truthfulness and quality of the collected information are evaluated based on the newly invented Bayesian Prospect Theory. The proposed methods and the system will be evaluated using real-world field data. The SOTERIA project will create new distributed control, optimization, and scalable resource management techniques in PSSs. The novelty lies in the integrated approach to efficiently managing resources considering human behavior and Tragedy of the Commons phenomena about shared resources, thus enhancing the victim’s satisfaction instead of utility maximization. To deal with incomplete information about resource availability, the proposed reinforcement learning techniques will enhance the victim’s decision-making capability in real time. Research outcomes of this project have tremendous potential for supporting ECC activities and saving peoples’ lives and infrastructures during and after disasters, by designing robust situation-aware disaster response networks and advancing state of the art research in Prospect Theory, Tragedy of the Commons, and Satisfaction Games. The project will train undergraduate and graduate students and the research findings will be disseminated via a project website and high-quality publications.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.