With the continuous advancement of network technology, various emerging complex networking optimization problems have created a wide range of applications utilizing game theory. However, since game theory is a mathematical framework, game theory-based solutions often rely heavily on the experience and knowledge of human experts. Recently, the remarkable advantages exhibited by generative artificial intelligence (GAI) have gained widespread attention. In this work, we propose a novel GAI-enabled game theory solution that combines the powerful reasoning and generation capabilities of GAI to the design and optimization of mobile networking. Specifically, we first outline the game theory and key technologies of GAI, and explore the advantages of combining GAI with game theory. Then, we review the contributions and limitations of existing research and demonstrate the potential application values of GAI applied to game theory in mobile networking. Subsequently, we develop a large language model (LLM)-enabled game theory framework to realize this combination, and demonstrate the effectiveness of the proposed framework through a case study in secured UAV networks. Finally, we provide several directions for future extensions.

翻译：随着网络技术的持续进步，各种新兴的复杂网络优化问题催生了博弈论的广泛应用。然而，由于博弈论是一个数学框架，基于博弈论的解决方案通常严重依赖人类专家的经验和知识。近年来，生成式人工智能展现出的显著优势引起了广泛关注。在本工作中，我们提出了一种新颖的生成式人工智能赋能的博弈论解决方案，它将生成式人工智能强大的推理和生成能力与移动网络的设计和优化相结合。具体而言，我们首先概述了博弈论和生成式人工智能的关键技术，并探讨了将生成式人工智能与博弈论结合的优势。接着，我们回顾了现有研究的贡献与局限性，并展示了生成式人工智能应用于博弈论在移动网络中的潜在应用价值。随后，我们开发了一个大型语言模型赋能的博弈论框架来实现这种结合，并通过一个安全无人机网络中的案例研究证明了所提框架的有效性。最后，我们提出了几个未来扩展的方向。