  The large language model (LLM) based agents have demonstrated their capacity
to automate and expedite software development processes. In this paper, we
focus on game development and propose a multi-agent collaborative framework,
dubbed GameGPT, to automate game development. While many studies have
pinpointed hallucination as a primary roadblock for deploying LLMs in
production, we identify another concern: redundancy. Our framework presents a
series of methods to mitigate both concerns. These methods include dual
collaboration and layered approaches with several in-house lexicons, to
mitigate the hallucination and redundancy in the planning, task identification,
and implementation phases. Furthermore, a decoupling approach is also
introduced to achieve code generation with better precision.

Artificial Intelligence