CAREER: Evaluating Cooperative Intelligence in Connected Communities

该项目探索了一种愿景，即建筑群自主合作，共享太阳能电池板、电池或发电机等能源。通过多智能体模拟和现实世界的实验，它旨在揭示合作如何在自组织能源系统中出现和持续，以及它如何导致集体利益，如节能和气候适应。通过利用集体努力，这项工作旨在促进向集体基础设施系统的转变。除了有针对性的科学贡献，该项目还包括一个互动教育计划，其中包括游戏和模拟，以促进公众对合作的理解，这是能源公平和可持续发展的一个重要方面。其目标是使建筑师、规划师和政策制定者能够利用知识和工具来设计和管理互联社区，在这些社区中，建筑物共享而不是竞争能源。该项目旨在激发一种新的思维方式，即集体合作如何创造更好的能源系统。该项目将探讨如何在战略性地汇集分布式能源（DER）的建筑群之间开展合作并保持合作，以增强共同的韧性和可持续性。它将建立一个跨学科框架，以调查多代理能源系统内的合作。该技术方法协同结合了基于强化学习的控制策略、多智能体模拟和经验验证。它试图正式建模复杂的互惠互动的基础上的合作能源行为连接的社区。总体目标是阐明定量设计原则和政策指导方针，将合作智能嵌入工程化的自组织架构中，以增强集体弹性和公平的资源分配。该项目的第一个重点是开发一个适应性强的模拟测试平台，以评估各种能源管理方案，社区配置和决策协议下的合作轨迹。这个灵活的虚拟试验平台将使系统的评估影响紧急合作的因素。第二个推力需要一个实证分析，以诊断如何现实世界的社会技术元素，从人类的喜好，技术扩散不对称形状合作的成果。基于数据的见解将揭示可操作的实施途径。最后，基于建构主义学习的互动网络平台和游戏将培养公众对分散系统和合作情报的理解，以实现公平和有弹性的能源获取。通过整合技术和社会层面的见解，该项目将为设计高效、有效的互联社区提供信息，并促进可持续、公平的能源系统。通过阐明本地化共享和能源管理的战略，该项目将展示分布式所有权和治理的模式。该奖项反映了NSF的法定使命，并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，被认为值得支持。

This project explores a vision where groups of buildings autonomously cooperate to share energy resources such as solar panels, batteries, or generators. Through multi-agent simulations and real-world experiments, it aims to reveal how cooperation can emerge and persist within self-organizing energy systems, and how it can lead to collective benefits such as energy savings and climate adaptation. By harnessing collective efforts, this work aims to catalyze a shift towards collective infrastructure systems. Beyond its targeted scientific contributions, the project includes an interactive educational program featuring games and simulations fostering public understanding of cooperation as a vital aspect for energy equity and sustainability. The goal is for findings to empower architects, planners, and policymakers with knowledge and tools to design and manage connected communities where buildings share, rather than compete for, energy resources. The project aspires to inspire a new way of thinking about how collective collaboration can create better energy systems.This project will investigate how cooperation can emerge and be sustained among groups of buildings that strategically pool distributed energy resources (DERs) to enhance shared resilience and sustainability. It will establish an interdisciplinary framework to investigate cooperation within multi-agent energy systems. The technical approach synergistically combines reinforcement learning-based control policies, multi-agent simulations, and empirical validation. It seeks to formally model the complex reciprocal interactions underlying cooperative energy behaviors within connected communities. The overarching goal is to elucidate quantitative design principles and policy guidelines that embed cooperative intelligence within engineered, self-organizing architectures to enhance collective resilience and equitable resource allocation. The first thrust of the project involves developing an adaptable simulation testbed to evaluate cooperation trajectories under various energy management schemes, community configurations, and decision protocols. This flexible virtual testbed will enable systematic evaluation of factors that influence emergent cooperation. The second thrust entails an empirical analysis to diagnose how real-world socio-technical elements—from human preferences to technology diffusion asymmetries—shape cooperative outcomes. Grounding insights in data will uncover actionable pathways for implementation. Finally, interactive web platforms and games based on constructivist learning will cultivate public understanding of decentralized systems and cooperative intelligence for equitable and resilient energy access. By integrating insights across technical and social dimensions, this project will inform the design of efficient, effective connected communities and foster sustainable, equitable energy systems. By elucidating strategies for localized sharing and energy management, the project will showcase models of distributed ownership and governance.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.