带状态反射的生产与碳减排的平均场斯塔克尔伯格博弈
Mean Field Stackelberg Game for Production and Carbon Emission Reduction with State Reflections
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中文总结 AI 辅助
针对带跨界污染与不可逆损害的全球变暖问题，提出含控制量平均场交互与共同噪声的两级斯塔克尔伯格博弈，通过反射机制执行排放上限，证明近似均衡存在性并经蒙特卡洛模拟分析敏感性，为生产与碳减排决策提供方法支持。
中文摘要 AI 辅助
由具有跨界污染特征且损害不可逆的人为碳排放驱动的全球变暖，对人类社会构成生存威胁。本文提出一种新型两级斯塔克尔伯格博弈，包含控制量的平均场交互与共同噪声，整合了状态反射排放动态下的层级决策。一个中央监管者（领导者）调整产品价格以引导n个异质性竞争区域（跟随者），同时通过反射机制执行严格的排放上限，该机制通过局部时间过程模拟应急减排。我们证明了近似斯塔克尔伯格均衡的存在性，并通过蒙特卡洛模拟开展敏感性分析。
英文摘要
Global warming, driven by anthropogenic carbon emissions with transboundary pollution characteristics and irreversible damage, poses an existential threat to human society. This paper develops a novel two-level Stackelberg game with mean field interaction of controls and common noise which integrates hierarchical decision-making under a state-reflected emission dynamics. A central regulator (leader) adjusts product prices to guide $n$ heterogeneous competing regions (followers) while enforcing a hard emission cap via a reflection mechanism that models emergency reductions through a local time process. We establish the existence of an approximate Stackelberg equilibrium and perform sensitivity analysis via Monte Carlo simulations.
