GameGPT: Multi-agent Collaborative Framework for Game Development

2023/10/12 by Dake Chen, Haoyang Zhang, Chen, Dake +8 · 10 citations
Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Multi-Agent Systems and Negotiation #Open Source Software Innovations #Software Engineering Research

paper · pdf · doi:10.48550/arxiv.2310.08067

openalex publication_date 2023/10/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

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.

Cited by

• The Era of Agentic Organization: Learning to Organize with Language Models
• The FM Agent
• V-GameGym: Visual Game Generation for Code Large Language Models
• FAIRGAMER: Evaluating Biases in the Application of Large Language Models to Video Games
• Automated Unity Game Template Generation from GDDs via NLP and Multi-Modal LLMs
• Communicative Agents for Slideshow Storytelling Video Generation based on LLMs
• Parallelism Meets Adaptiveness: Scalable Documents Understanding in Multi-Agent LLM Systems
• Multi-Agent Game Generation and Evaluation via Audio-Visual Recordings
• Co-Saving: Resource Aware Multi-Agent Collaboration for Software Development
• Grounding Machine Creativity in Game Design Knowledge Representations: Empirical Probing of LLM-Based Executable Synthesis of Goal Playable Patterns under Structural Constraints

Related

• MindAgent: Emergent Gaming Interaction
• OpenGame: Open Agentic Coding for Games
• A Survey on Large Language Model-Based Game Agents
• Cooperation on the Fly: Exploring Language Agents for Ad Hoc Teamwork in the Avalon Game
• GVGAI-LLM: Evaluating Large Language Model Agents with Infinite Games