arXiv Open Access 2025

Game Theory Meets Large Language Models: A Systematic Survey with Taxonomy and New Frontiers

Haoran Sun Yusen Wu Peng Wang Wei Chen Yukun Cheng +2 lainnya
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Abstrak

Game theory is a foundational framework for analyzing strategic interactions, and its intersection with large language models (LLMs) is a rapidly growing field. However, existing surveys mainly focus narrowly on using game theory to evaluate LLM behavior. This paper provides the first comprehensive survey of the bidirectional relationship between Game Theory and LLMs. We propose a novel taxonomy that categorizes the research in this intersection into four distinct perspectives: (1) evaluating LLMs in game-based scenarios; (2) improving LLMs using game-theoretic concepts for better interpretability and alignment; (3) modeling the competitive landscape of LLM development and its societal impact; and (4) leveraging LLMs to advance game models and to solve corresponding game theory problems. Furthermore, we identify key challenges and outline future research directions. By systematically investigating this interdisciplinary landscape, our survey highlights the mutual influence of game theory and LLMs, fostering progress at the intersection of these fields.

Topik & Kata Kunci

Penulis (7)

H

Haoran Sun

Y

Yusen Wu

P

Peng Wang

W

Wei Chen

Y

Yukun Cheng

X

Xiaotie Deng

X

Xu Chu

Format Sitasi

Sun, H., Wu, Y., Wang, P., Chen, W., Cheng, Y., Deng, X. et al. (2025). Game Theory Meets Large Language Models: A Systematic Survey with Taxonomy and New Frontiers. https://arxiv.org/abs/2502.09053

Akses Cepat

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Informasi Jurnal
Tahun Terbit
2025
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓