With the continuous advancement of network technology, various emerging complex networking optimization problems opened up a wide range of applications utilizating of game theory. However, since game theory is a mathematical framework, game theory-based solutions often require the experience and knowledge of human experts. Recently, the remarkable advantages exhibited by generative artificial intelligence (GAI) have gained widespread attention. In this article, 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 then explore the advantages of combining GAI with game theory. Then, we briefly review the advantages and limitations of existing research and demonstrate the potential application values of GAI applied to game theory in mobile networking. Subsequently, we develop a game theory framework enabled by large language models (LLMs) 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基于博弈论的广泛应用。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需要人类专家的经验和知识。近年来，生成式人工智能（GAI）展现出的显著优势引起了广泛关注。在本文中，我们提出了一种新颖的基于GAI的博弈论解决方案，将GAI强大的推理和生成能力结合到移动网络的设计与优化中。具体来说，我们首先概述了博弈论和GAI的关键技术，然后探讨了将GAI与博弈论相结合的优势。接着，我们简要回顾了现有研究的优势与局限性，并展示了GAI在移动网络中应用于博弈论的潜在应用价值。随后，我们开发了一个由大语言模型（LLMs）驱动的博弈论框架以实现这种结合，并通过一个安全无人机网络的案例研究证明了所提出框架的有效性。最后，我们指出了未来扩展的几个方向。