This paper presents the second ChatGPT4PCG competition at the 2024 IEEE
Conference on Games. In this edition of the competition, we follow the first
edition, but make several improvements and changes. We introduce a new
evaluation metric along with allowing a more flexible format for participants'
submissions and making several improvements to the evaluation pipeline.
Continuing from the first edition, we aim to foster and explore the realm of
prompt engineering (PE) for procedural content generation (PCG). While the
first competition saw success, it was hindered by various limitations; we aim
to mitigate these limitations in this edition. We introduce diversity as a new
metric to discourage submissions aimed at producing repetitive structures.
Furthermore, we allow submission of a Python program instead of a prompt text
file for greater flexibility in implementing advanced PE approaches, which may
require control flow, including conditions and iterations. We also make several
improvements to the evaluation pipeline with a better classifier for similarity
evaluation and better-performing function signatures. We thoroughly evaluate
the effectiveness of the new metric and the improved classifier. Additionally,
we perform an ablation study to select a function signature to instruct ChatGPT
for level generation. Finally, we provide implementation examples of various PE
techniques in Python and evaluate their preliminary performance. We hope this
competition serves as a resource and platform for learning about PE and PCG in
general.

该研究论文介绍了 2024 年 IEEE 游戏会议上的第二届 ChatGPT4PCG 竞赛，它旨在推动和探索面向程序化内容生成的提示工程。通过引入多样性度量、允许提交 Python 程序以及改进评估流程等措施，该竞赛旨在解决第一届竞赛中的限制问题，同时对新度量和改进评估器的有效性进行评估，并通过消融研究选择函数签名来指导 ChatGPT 进行关卡生成。