Game Theory Meets Large Language Models: A Systematic Survey with Taxonomy and New Frontiers
This survey addresses the need for a broader understanding of how game theory and LLMs interact, which is incremental as it synthesizes existing work but introduces a new taxonomy.
This paper tackles the lack of comprehensive surveys on the bidirectional relationship between game theory and large language models (LLMs) by providing a systematic survey with a novel taxonomy categorizing research into four perspectives, fostering progress in this interdisciplinary field.
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.