Game Development as Human-LLM Interaction
<|reference_start|>Game Development as Human-LLM Interaction: Game development is a highly specialized task that relies on a complex game engine powered by complex programming languages, preventing many gaming enthusiasts from handling it. This paper introduces the Interaction-driven Game Engine (IGE) powered by LLM, which allows everyone to develop a custom game using natural language through Human-LLM interaction. To enable an LLM to function as an IGE, we instruct it to perform the following processes in each turn: (1) $P_{script}$ : configure the game script segment based on the user's input; (2) $P_{code}$ : generate the corresponding code snippet based on the game script segment; (3) $P_{utter}$ : interact with the user, including guidance and feedback. We propose a data synthesis pipeline based on the LLM to generate game script-code pairs and interactions from a few manually crafted seed data. We propose a three-stage progressive training strategy to transfer the dialogue-based LLM to our IGE smoothly. We construct an IGE for poker games as a case study and comprehensively evaluate it from two perspectives: interaction quality and code correctness. The code and data are available at \url{https://github.com/alterego238/IGE}.<|reference_end|>
@article{hong2024game,
    title={Game Development as Human-LLM Interaction},
    author={Jiale Hong, Hongqiu Wu, Hai Zhao},
    journal={arXiv preprint arXiv:2408.09386},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.09386},
    primaryClass={cs.AI cs.CL cs.HC}
}