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Computer Science > Computation and Language

arXiv:2305.18243 (cs)
[Submitted on 20 May 2023 (v1), last revised 2 Jul 2023 (this version, v3)]

Title:Practical PCG Through Large Language Models

Authors:Muhammad U Nasir, Julian Togelius
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Abstract:Large Language Models (LLMs) have proven to be useful tools in various domains outside of the field of their inception, which was natural language processing. In this study, we provide practical directions on how to use LLMs to generate 2D-game rooms for an under-development game, named Metavoidal. Our technique can harness the power of GPT-3 by Human-in-the-loop fine-tuning which allows our method to create 37% Playable-Novel levels from as scarce data as only 60 hand-designed rooms under a scenario of the non-trivial game, with respect to (Procedural Content Generation) PCG, that has a good amount of local and global constraints.
Comments: Published at 2023 IEEE Conference on Games
Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2305.18243 [cs.CL]
  (or arXiv:2305.18243v3 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2305.18243

Submission history

From: Muhammad Umair Nasir Mr. [view email]
[v1] Sat, 20 May 2023 16:08:45 UTC (4,608 KB)
[v2] Wed, 31 May 2023 06:05:03 UTC (4,608 KB)
[v3] Sun, 2 Jul 2023 09:11:17 UTC (4,609 KB)
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