Creating programs to represent board games can be a time-consuming task. Large Language Models (LLMs) arise as appealing tools to expedite this process, given their capacity to efficiently generate code from simple contextual information. In this work, we propose a method to test how capable three LLMs (Claude, DeepSeek and ChatGPT) are at creating code for board games, as well as new variants of existing games.
@article{arxiv.2511.05114,
title = {Usando LLMs para Programar Jogos de Tabuleiro e Varia\c{c}\~oes},
author = {Álvaro Guglielmin Becker and Lana Bertoldo Rossato and Anderson Rocha Tavares},
journal= {arXiv preprint arXiv:2511.05114},
year = {2025}
}
Comments
Accepted for presentation at the I Escola Regional de Aprendizado de M\'aquina e Intelig\^encia Artificial da Regi\~ao Sul, 2025, in Portuguese language