CRII: RI: Strategic Interaction in Adversarial Settings with Information Hubs.

为了确保安全、公共安全和环境的可持续性，执法和安全机构往往以非常有限的预算和资源打击非法活动，如攻击关键基础设施、城市犯罪、偷猎和非法砍伐。先进的博弈论模型和算法已经被开发出来，用于分析此类场景中的威胁，这些场景可以描述为有攻击者和防御者。这些技术在帮助防御者分配资源抵御威胁方面一直是有效的。现在，在一个由社交网络主导的现代信息环境中，捍卫者需要考虑在收集、处理和传播信息的环境中“信息枢纽”(IHS)的影响。IHS包括不断增长的“物联网”中的各种互联设备，以及社交网络中的人们。该项目旨在设计新的博弈论模型来解释IHS对攻防双方互动的影响，并开发方法来帮助防守者优化选择和分配IHS以获得最佳的防御效果。该项目还将开发方法，在IHS存在的情况下寻找最佳的防守单位分配，以便防守方能够用最少的资源获得最大的利益。为了充分理解IHS在对抗性环境中的作用，研究人员将(1)开发新的博弈论方法，扩展Stackelberg安全博弈等模型，使IHS能够与代理进行通信；(2)从理论上分析优化选择和分配IHS以最大化防御者在游戏中的预期效用的计算复杂性，并提供基于混合整数线性规划(MILP)的解决方法来计算最优选择和分配，以及针对大规模问题实例的近似方案和启发式算法；以及(3)开发基于MILP的算法来计算针对信息收集、处理和传播中的不确定性的稳健策略。研究人员将在模拟和现实世界保护场景中对新算法进行评估。这一奖项反映了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。

To ensure security, public safety, and environmental sustainability, law enforcement and security agencies often operate with a very limited budget and resources to combat illegal activities such as attacks on critical infrastructure, urban crimes, poaching, and illegal logging. Advanced game-theoretic models and algorithms have been developed for analyzing threats in such scenarios that can be described as having attackers and defenders. These techniques have been effective in helping defenders allocate resources to defend against threats. Now, in a modern information environment dominated by social networks and increased connectivity in all aspects of life, defenders will need to consider the influence of the "information hubs" (IHs) in that environment that collect, process and disseminate information. IHs include all sorts of connected devices in the growing "Internet of Things", as well as the people in the social networks. This project aims to design new game theoretic models that account for the influence of IHs on attacker-defender interactions and develop methods to help the defender optimally select and allocate IHs for best defensive effect. This project will also develop methods to find the optimal allocation of defensive units given the presence of IHs so that the defender can achieve maximal benefit with minimal resources. Towards gaining a full understanding of the role of IHs in adversarial settings, the researchers will (1) develop new game-theoretic approaches that extend models such as Stackelberg security games to allow the IHs to communicate with the agents; (2) theoretically analyze the computational complexity of optimally selecting and allocating IHs to maximize the defender's expected utility in the game, and provide Mixed Integer Linear Programming (MILP)-based solution approach to compute the optimal selection and allocation, as well as approximation schemes and heuristic algorithms for large-scale problem instances; and (3) develop MILP-based algorithms to compute robust strategies against uncertainties in information collection, processing and dissemination. The researchers will evaluate the new algorithms both in simulation and for real-world conservation scenarios.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.