Summary of Gpt For Games: An Updated Scoping Review (2020-2024), by Daijin Yang et al.
GPT for Games: An Updated Scoping Review (2020-2024)
by Daijin Yang, Erica Kleinman, Casper Harteveld
First submitted to arxiv on: 1 Nov 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This scoping review explores the applications of Generative Pre-training Transformer (GPT) models in games, analyzing 177 articles, with 122 published in 2024. The study identifies five prominent areas: procedural content generation, mixed-initiative game design, mixed-initiative gameplay, playing games, and game user research. By synthesizing insights from these applications, the paper proposes future studies focus on expanding GPT model capabilities and investigating complex interactions between AI and users. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at how a special type of artificial intelligence called Generative Pre-training Transformer (GPT) is used in video games. Researchers looked at 177 articles to see what people are doing with GPT in gaming. They found that it’s being used in five main ways: making game content, designing interactive games, playing games against other players or AI, and studying how people play games. The researchers think that future studies should focus on making the GPT models better and understanding how they work together with gamers. |
Keywords
» Artificial intelligence » Gpt » Transformer
