Large Language Models and Video Games: A Preliminary Scoping Review

LLMs are powerful tools for language processing and prediction, pre-trained on vast collections of natural language, and capable of performing diverse language analysis and generation tasks [23]. The release of ChatGPT, along with the many other available LLMs (e.g., GPT-4, LLaMa, Codex, BERT) has opened new doors to research and development potential, which has seen a recent increase in related research. Like many fields, LLMs hold interesting possibilities for video games, which has prompted many researchers to hasten to investigate the potential for applying LLMs to various aspects of video game research and development. Although the concept of generative AI is not new to video games, with decades of prior work in AI-powered generation of game content [26, 46], LLMs have the potential to revolutionise generation and co-creation of video game content, along with game development tools and processes, and games research approaches. As research and development of LLMs and games is occurring and evolving quickly, it is difficult to capture a full picture of how LLMs are being used in games research. The aim of this paper is to provide a preliminary scoping review of LLMs and video games, surveying the related research conducted between 2020 and 2023. We aim to identify the ways in which researchers have been exploring the use of LLMs for game development and research to date. To identify the relevant papers, we conducted a Google Scholar search for papers published between 2020-2023 (and very early 2024). We identified 76 relevant papers from 2260 results returned in the search.