首次系统梳理博弈论与大模型的双向互动关系。
Game Theory Meets Large Language Models: A Systematic Survey with Taxonomy and New Frontiers
- 提出四维分类体系，涵盖评估、优化、生态建模与问题求解。
- 揭示大模型与博弈论相互赋能的新范式，推动跨领域融合。
- 适合关注人工智能治理、对齐与战略决策的研究者阅读。
博弈论是分析策略互动的基础框架，其与大语言模型（LLMs）的交叉已成为快速发展的领域。现有综述多局限于用博弈论评估大模型行为。本文首次提供该交叉领域的全面综述，提出一种新颖的分类体系，将研究分为四个维度：(1) 在博弈场景中评估大模型表现；(2) 运用博弈论概念提升大模型可解释性与对齐性；(3) 建模大模型研发的竞合格局及其社会影响；(4) 利用大模型推进博弈模型发展并求解博弈理论问题。同时识别关键挑战，展望未来方向。通过系统性考察这一跨学科领域，本综述凸显了博弈论与大模型之间的相互塑造作用，促进两领域协同发展。
原文摘要 · Abstract (English)
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.
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