Usando LLMs para Programar Jogos de Tabuleiro e Variações
Resumo
A criação de programas que representem jogos de tabuleiro pode ser uma tarefa demorada. Large Language Models (LLMs) surgem como ferramentas interessantes para acelerar esse processo, dada sua capacidade para geração eficaz de código a partir de informações contextuais simples. Neste trabalho, propomos um método para testar a capacidade de três LLMs (Claude, DeepSeek e ChatGPT) de criar código para jogos de tabuleiro, bem como de novas variantes de jogos existentes.Referências
Anthropic (2024). The Claude 3 Model Family: Opus, Sonnet, Haiku. [link]. [Accessed 21-04-2025].
Becker, Á. G., de Oliveira, G. B., Rossato, L. B., and Tavares, A. R. (2025). Boardwalk: Towards a Framework for Creating Board Games with LLMs. In SBGames. To appear. Pre-print: [link].
Browne, C. (2011). Evolutionary Game Design. SpringerBriefs in Computer Science. Springer London, London, UK.
Coignion, T., Quinton, C., and Rouvoy, R. (2024). A Performance Study of LLM-Generated Code on Leetcode. In Proceedings of the 28th EASE, pages 79–89.
Genesereth, M., Love, N., and Pell, B. (2005). General game playing: Overview of the AAAI competition. AI magazine, 26(2):62–62.
Liu, A. et al. (2025). DeepSeek-V3 Technical Report.
Nielsen, J. L., Jensen, B. F., Mahlmann, T., Togelius, J., and Yannakakis, G. N. (2014). AI for General Strategy Game Playing, chapter 10, pages 274–304. John Wiley & Sons, Ltd.
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Piette, E., Soemers, D., Stephenson, M., Sironi, C., Winands, M., and Browne, C. (2020). Ludii – the ludemic general game system. Frontiers in Artificial Intelligence and Applications, 325:411–418.
Rossato, L. B., Bombardelli, L. B., and Tavares, A. R. (2023). Evolutionary Tabletop Game Design: A Case Study in the Risk Game. In SBGames, page 161–170, New York, NY, USA. Association for Computing Machinery.
Tanaka, T. and Simo-Serra, E. (2024). Grammar-based game description generation using large language models. IEEE Transactions on Games, pages 1–14.
Todd, G., Padula, A. G., Stephenson, M., Piette, É., Soemers, D., and Togelius, J. (2024). GAVEL: Generating games via evolution and language models. NeurIPS, 37:110723–110745.
Becker, Á. G., de Oliveira, G. B., Rossato, L. B., and Tavares, A. R. (2025). Boardwalk: Towards a Framework for Creating Board Games with LLMs. In SBGames. To appear. Pre-print: [link].
Browne, C. (2011). Evolutionary Game Design. SpringerBriefs in Computer Science. Springer London, London, UK.
Coignion, T., Quinton, C., and Rouvoy, R. (2024). A Performance Study of LLM-Generated Code on Leetcode. In Proceedings of the 28th EASE, pages 79–89.
Genesereth, M., Love, N., and Pell, B. (2005). General game playing: Overview of the AAAI competition. AI magazine, 26(2):62–62.
Liu, A. et al. (2025). DeepSeek-V3 Technical Report.
Nielsen, J. L., Jensen, B. F., Mahlmann, T., Togelius, J., and Yannakakis, G. N. (2014). AI for General Strategy Game Playing, chapter 10, pages 274–304. John Wiley & Sons, Ltd.
OpenAI et al. (2024). GPT-4 Technical Report.
Piette, E., Soemers, D., Stephenson, M., Sironi, C., Winands, M., and Browne, C. (2020). Ludii – the ludemic general game system. Frontiers in Artificial Intelligence and Applications, 325:411–418.
Rossato, L. B., Bombardelli, L. B., and Tavares, A. R. (2023). Evolutionary Tabletop Game Design: A Case Study in the Risk Game. In SBGames, page 161–170, New York, NY, USA. Association for Computing Machinery.
Tanaka, T. and Simo-Serra, E. (2024). Grammar-based game description generation using large language models. IEEE Transactions on Games, pages 1–14.
Todd, G., Padula, A. G., Stephenson, M., Piette, É., Soemers, D., and Togelius, J. (2024). GAVEL: Generating games via evolution and language models. NeurIPS, 37:110723–110745.
Publicado
12/11/2025
Como Citar
BECKER, Álvaro Guglielmin; ROSSATO, Lana Bertoldo; TAVARES, Anderson Rocha.
Usando LLMs para Programar Jogos de Tabuleiro e Variações. In: ESCOLA REGIONAL DE APRENDIZADO DE MÁQUINA E INTELIGÊNCIA ARTIFICIAL DA REGIÃO SUL (ERAMIA-RS), 1. , 2025, Porto Alegre/RS.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 320-323.
DOI: https://doi.org/10.5753/eramiars.2025.16679.
