Cyber-Physical System (CPS) represents systems that join both hardware and software components to perform real-time services. Maintaining the system's reliability is critical to the continuous delivery of these services. However, the CPS running environment is full of uncertainties and can easily lead to performance degradation. As a result, the need for a recovery technique is highly needed to achieve resilience in the system, with keeping in mind that this technique should be as green as possible. This early doctorate proposal, suggests a game theory solution to achieve resilience and green in CPS. Game theory has been known for its fast performance in decision-making, helping the system to choose what maximizes its payoffs. The proposed game model is described over a real-life collaborative artificial intelligence system (CAIS), that involves robots with humans to achieve a common goal. It shows how the expected results of the system will achieve the resilience of CAIS with minimized CO2 footprint.

翻译：网络物理系统（CPS）是融合硬件与软件组件以提供实时服务的系统。维持系统可靠性对于持续交付这些服务至关重要。然而，CPS运行环境充满不确定性，极易导致性能下降。因此，亟需一种既能实现系统韧性又尽可能环保的恢复技术。本项早期博士研究提出了一种基于博弈论的解决方案，旨在实现网络物理系统的韧性与绿色性。博弈论以其在决策中的快速性能而闻名，可帮助系统选择使其收益最大化的方案。所提出的博弈模型描述了一个涉及人机协作实现共同目标的真实协作人工智能系统（CAIS）。研究展示了该系统预期结果如何在最小化二氧化碳足迹的同时实现CAIS的韧性。