CAREER: Psychology-aware Human-in-the-Loop Cyber-Physical-System (HCPS): Methodologies, Algorithms, and Deployment

职业：具有心理学意识的人在环网络物理系统 (HCPS)：方法、算法和部署

• 批准号: 2339266
• 负责人: Salma Elmalaki
• 金额: $ 57.5万
• 依托单位: University of California-Irvine
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-01 至 2028-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2339266&HistoricalAwards=false
• 关键词: CAREER; Psychology; aware; Human; Loop

The seamless interaction between humans and smart technologies represents a significant opportunity, but it also presents a daunting set of challenges. Understanding the intricate interactions between CPS and humans is essential for shaping the ultimate societal outcomes of future CPS technologies, particularly within the realm of Human-Cyber-Physical Systems (HCPS). In this context, decisions made by CPS can yield disparate impacts on individuals within settings like smart cities, traffic systems, and crowd management, constituting what we term as "Multi-Human-CPS (MHCPS)." In particular, MHCPS encapsulates a multitude of individuals with conflicting preferences and diverse perceptions coexisting within the same environment, influenced by both social-psychological dynamics and the decision-making process of CPS. MHCPS consists of two intertwined and coupled dynamics, physical and social psychology, the latter encapsulating the ever-changing patterns of social interactions that mold individuals' thoughts, feelings, and behaviors along the continuum of altruistic, prosocial, neutral, or antisocial behavior. Research underscores the impact of social-psychological states on overall system performance, where increased prosocial behavior correlates with heightened system compliance and acceptance. The objective of this research is to design CPS decision-making algorithms that understand both the physical system and the social-psychological nature of human interactions with these systems. Such psychology-aware decision-making algorithms will enable harmonious interactions, foster equity, and optimize overall performance.This NSF CAREER project aims to bridge a gap in current CPS engineering practices by incorporating social-psychological dynamics and societal tensions into engineering solutions to address current and future challenges of societal scale CPS. This research introduces new algorithms, models, and tools that integrate these dynamics into engineering solutions, significantly expanding the research toolbox available to both researchers and practitioners. The research entails: (i) developing novel human modeling techniques to capture social psychological dynamics in Multi-Human CPS (MHCPS) applications, (ii) formalizing objectives for CPS decision-making to enhance social dynamics in MHCPS, (iii) designing neurosymbolic sequential decision-making algorithms that account for both physical and social dynamics and constraints in MHCPS, (iv) creating causality-aware preference learning algorithms to capture tradeoffs and social tensions in MHCPS, (v) deploying decision-making algorithms in real-life applications, considering deployment/resource constraints and their impact on the resulting system, and (vi) implementing systematic software frameworks to facilitate the real-life implementation of MHCPS. This research can influence the direction of engineering research significantly, advancing the understanding and development of CPS technologies with enhanced social considerations.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.

人类与智能技术之间的无缝互动代表了一个重要的机会，但它也带来了一系列艰巨的挑战。了解CPS和人类之间的复杂相互作用对于塑造未来CPS技术的最终社会成果至关重要，尤其是在人类周期系统（HCP）领域内。在这种情况下，CPS做出的决定可以对智能城市，交通系统和人群管理等环境中的个人产生不同的影响，这构成了我们所说的“多人CPS（MHCP）”。特别是，MHCP封装了许多具有冲突偏好和各种看法在同一环境中共存的个人，受社会心理动态和CPS决策过程的影响。 MHCP由两种相互交织和耦合的动态，物理和社会心理学组成，后者封装了社会互动的不断变化的模式，这些模式塑造了个人的思想，感受和行为，沿着无私，亲社会，中立或反社会行为的连续性。研究强调了社会心理状态对整体系统绩效的影响，在这种情况下，社会社会行为的增加与系统的依从性和接受程度的增强相关。这项研究的目的是设计CPS决策算法，这些算法既了解人类与这些系统的人类互动的身体系统和社会心理学性质。这种意识到心理学的决策算法将实现和谐的互动，促进公平并优化整体绩效。该NSF职业项目旨在通过将社会心理动力学和社会紧张局势融合到工程解决方案中，以应对社会规模CPS的当前和未来挑战。这项研究介绍了将这些动态整合到工程解决方案中的新算法，模型和工具，并大大扩展了研究人员和从业者可用的研究工具箱。研究需要：（i）开发新型的人类建模技术来捕获多人类CPS（MHCPS）应用中的社会心理动态，（ii）为CPS决策的形式化目标，以增强MHCP的社会动态，（III）构成神经偶然的决策算法，以构成物理性和社会性动力学，以创建MINTS MHC，并在MHC中创建MHC，以计入MHC，以计入MHC，以计入MHC，以计入MHC中，以计入MHC中，以计入MHC中，以计入MHC中，以计入MHC中，以计入MHC中，以计入MHC中，以计入MHC中，以计入MHC中，并在MHCP中构成了MHCS，并构成了MHC的构成效果。偏爱学习算法，以捕获MHCP中的权衡和社会紧张局势，（v）在现实生活应用中部署决策算法，考虑部署/资源限制及其对所得系统的影响，以及（VI）实施系统的软件框架以促进MHCP的现实生活实施。这项研究可以极大地影响工程研究的方向，以增强的社会考虑来推动CPS技术的理解和发展。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评估评估的评估来支持的。