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Large Language Models and Games: A Survey and Roadmap (arxiv.org)
3 points by abhas9 on Aug 31, 2024 | hide | past | pdf | discuss on HN

In plain words: This survey collects research on how large language models are used in games, sorting it by the roles models play, from game master to player to designer. It is the first full map of the field, pointing out untested ideas and weighing where these models help versus where they fall short.

Abstract

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.

Roberto Gallotta, Graham Todd, Marvin Zammit, Sam Earle, Antonios Liapis, Julian Togelius, Georgios N. Yannakakis
arXiv:2402.18659 · cs.CL, cs.AI, cs.HC · submitted Feb 28, 2024 · updated Dec 9, 2024
abstract · pdf · html · Accepted for publication at the IEEE Transactions on Games (19 pages, 6 figures)

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