Procedural generation of 2D levels using large language models - Fonseca Júnior, Marcelo Carlos da; Nunes, Luiz Fernando (Revista Terra & Cultura: Cadernos de Ensino e Pesquisa; Vol 41 No especial (2025): Ciência da Computação, 2025)
This study explores the use of Large Language Models (LLMs) for Procedural Content Generation (PCG) in digital games, specifically for creating levels for a 2D game similar to the classic The Legend of Zelda. The methodology includes the fine-tuning of the LLaMa 3.1 model using the Zelda-Level-Games dataset,adapting it for the generation of playable and customized levels through natural language, allowing level design manipulation based on input instructions. The evaluation was conducted using metrics of playability, novelty, diversity, and accuracy, showing that the model achieves good results in most metrics, although it faces challenges in accuracy, suggesting areas for future work. The results indicate that using LLMs for PCG is promising, especially as it enables customized content creation through natural language, contributing to accessibility and productivity in game design