Procedural Content Generation via Generative Artificial Intelligence
Quick summary
arXiv:2407.09013v3 Announce Type: replace Abstract: The attempt to utilize machine learning in procedural content generation (PCG) has been made in the past. In this survey paper, we investigate how generative artificial intelligence (AI), which saw a significant increase in interest in the mid-2010s, is being used for PCG. We review applications of generative AI for the creation of various types of content, including terrains, items, and even storylines. While generative AI is effective for PCG, building high-performance models requires not only handling customized content and ensuring qualit
Key takeaways
- arXiv:2407.09013v3 Announce Type: replace Abstract: The attempt to utilize machine learning in procedural content generation (PCG) has been made in the past.
- In this survey paper, we investigate how generative artificial intelligence (AI), which saw a significant increase in interest in the mid-2010s, is being used for PCG.
- We review applications of generative AI for the creation of various types of content, including terrains, items, and even storylines.
Why it matters
The value of this work lies as much in how it was tested as in the claim itself. Sample design, baselines, uncertainty and replication help separate a laboratory result from real-world impact.
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