Game Development as Human-LLM Interaction

• URL: http://arxiv.org/abs/2408.09386v1
• Date: Sun, 18 Aug 2024 07:06:57 GMT
• Title: Game Development as Human-LLM Interaction
• Authors: Jiale Hong, Hongqiu Wu, Hai Zhao,
• Abstract summary: This paper introduces the Interaction-driven Game Engine (IGE) powered by Human-LLM interaction. We construct an IGE for poker games as a case study and evaluate it from two perspectives: interaction quality and code correctness.
• Score: 55.03293214439741
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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}.

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