Digital Game Development Using Large Language Models (LLMs): An Exploratory Study
Resumo
Introduction: Large Language Models (LLMs) are powerful tools for automating tasks like documentation, code generation, and prototyping in computer science, but their integration into game development pipelines is an opportunity by, also a challenge. Objective: This paper presents the development and implementation of PromptingGameCraft (PGC), a tool that uses Large Language Models (LLMs) to automate key steps in digital game development. The tool takes a Game Design Document (GDD) as input and automatically generates a Game Design File (GDF) in JSON format, along with a custom class diagram, directory and file structure, and game code. Methodology: The architecture was implemented through a web interface connected to the DeepSeek-reasoner model API hosted on Google Cloud. As a proof of concept, a 2D ball-catching game with progressive difficulty was developed. Results: The automated generation process demonstrated efficiency in the transition from design to code, promoting modular organization, logical clarity, and reusability. In addition to productivity and standardization, PGC has the potential to democratize access to game development in educational, training, and community contexts. By enabling the accessible transformation of ideas into working prototypes, it promotes creative expression, supports active learning, and enhances participation among diverse groups.
Palavras-chave:
Large Language Models, Game Design, Game Prototyping, AI-Assisted Development
Referências
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Sahoo, P., Singh, A. K., Saha, S., Jain, V., Mondal, S., e Chadha, A. (2024). A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications. arXiv e-prints, page arXiv:2402.07927.
Salazar, M. G., Mitre, H. A., Olalde, C. L., e Sánchez, J. L. G. (2012). Proposal of game design document from software engineering requirements perspective. In 2012 17th International Conference on Computer Games (CGAMES), pages 81–85.
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Xu, F. F., Alon, U., Neubig, G., e Hellendoorn, V. J. (2022). A systematic evaluation of large language models of code. arXiv preprint arXiv:2202.13169.
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Chen, D., Wang, H., Huo, Y., Li, Y., e Zhang, H. (2023). Gamegpt: Multi-agent collaborative framework for game development. arXiv preprint arXiv:2310.08067.
Chen, W. et al. (2022). Program of thoughts prompting: Disentangling computation from reasoning for numerical reasoning tasks. arXiv preprint arXiv:2211.12588.
Fullerton, T. (2018). Game Design Workshop: A Playcentric Approach to Creating Innovative Games. AK Peters/CRC Press.
Gallotta, R., Liapis, A., e Yannakakis, G. (2024a). Consistent game content creation via function calling for large language models. In 2024 IEEE Conference on Games (CoG), pages 1–4. IEEE.
Gallotta, R., Todd, G., Zammit, M., Earle, S., Liapis, A., Togelius, J., e Yannakakis, G. N. (2024b). Large language models and games: A survey and roadmap. IEEE Transactions on Games.
Kojima, T., Schmid, P., Li, Q., Alsaidi, A., Tan, C., Lu, X., e Song, D. (2023). What makes chain-of-thought prompting effective? a counterfactual study. In Proceedings of the 11th International Conference on Learning Representations (ICLR).
Kumaran, V., Rowe, J., Mott, B., e Lester, J. (2023). Scenecraft: Automating interactive narrative scene generation in digital games with large language models. In Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, volume 19, pages 86–96.
Li, X. et al. (2023a). Chain of code: Reasoning with code for interpretability. arXiv preprint arXiv:2303.08168.
Li, X. et al. (2023b). Structured prompting: Scaling in-context learning to 1,000 examples. arXiv preprint arXiv:2303.08774.
Lima, E. S. d., Feijó, B., Casanova, M. A., e Furtado, A. L. (2023). Chatgeppetto - an ai-powered storyteller. In Proceedings of the 22nd Brazilian Symposium on Games and Digital Entertainment (SBGames), Rio Grande, Brazil. ACM.
Liu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., e Neubig, G. (2021). Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing. arXiv preprint arXiv:2107.13586.
Muratet, M. e Garbarini, D. (2020). Accessibility and serious games: What about entity-component-system software architecture? In Games and Learning Alliance (GALA). Springer.
Newzoo (2021). Global games market to generate $175.8 billion in 2021. Accessed: 2025-04-17.
Nye, M. et al. (2021). Show your work: Scratchpads for intermediate computation with language models. In Advances in Neural Information Processing Systems.
Redmond, P., Castello, J., Calderón Trilla, J. M., e Kuper, L. (2024). Exploring the theory and practice of concurrency in the entity-component-system pattern. Proceedings of the ACM on Programming Languages, 8(OOPSLA):1–29.
Sahoo, P., Singh, A. K., Saha, S., Jain, V., Mondal, S., e Chadha, A. (2024). A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications. arXiv e-prints, page arXiv:2402.07927.
Salazar, M. G., Mitre, H. A., Olalde, C. L., e Sánchez, J. L. G. (2012). Proposal of game design document from software engineering requirements perspective. In 2012 17th International Conference on Computer Games (CGAMES), pages 81–85.
Tower, S. (2021). State of mobile gaming 2021. Accessed: 2025-04-17.
Worldpay (2021). Microtransactions: Next big thing? Accessed: 2025-04-17.
Xu, F. F., Alon, U., Neubig, G., e Hellendoorn, V. J. (2022). A systematic evaluation of large language models of code. arXiv preprint arXiv:2202.13169.
Yao, S., Zhao, J., Yu, D., Yu, S., Gao, S., Zettlemoyer, L., e Narasimhan, K. (2022). React: Synergizing reasoning and acting in language models. arXiv preprint arXiv:2210.03629.
Publicado
30/09/2025
Como Citar
SERRA, Cristiano Barroso; SERRA, Gabriel Mattos Barroso; CLASSE, Tadeu Moreira de.
Digital Game Development Using Large Language Models (LLMs): An Exploratory Study. In: SIMPÓSIO BRASILEIRO DE JOGOS E ENTRETENIMENTO DIGITAL (SBGAMES), 24. , 2025, Salvador/BA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 538-549.
DOI: https://doi.org/10.5753/sbgames.2025.9992.
