Large Language Models and Games: A Survey and Roadmap
Roberto Gallotta Graham Todd Marvin Zammit Sam Earle Antonios Liapis Julian Togelius Georgios N. Yannakakis
Recent years have seen an explosive increase in research on large language
models (LLMs), and accompanying public engagement on the topic. While starting
as a niche area within natural language processing, LLMs have shown remarkable
potential across a broad range of applications and domains, including games.
This paper surveys the current state of the art across the various applications
of LLMs in and for games, and identifies the different roles LLMs can take
within a game. Importantly, we discuss underexplored areas and promising
directions for future uses of LLMs in games and we reconcile the potential and
limitations of LLMs within the games domain. As the first comprehensive survey
and roadmap at the intersection of LLMs and games, we are hopeful that this
paper will serve as the basis for groundbreaking research and innovation in
this exciting new field.