Summary of Pangea: Procedural Artificial Narrative Using Generative Ai For Turn-based Video Games, by Steph Buongiorno et al.
PANGeA: Procedural Artificial Narrative using Generative AI for Turn-Based Video Games
by Steph Buongiorno, Lawrence Jake Klinkert, Tanishq Chawla, Zixin Zhuang, Corey Clark
First submitted to arxiv on: 30 Apr 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL)
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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 research introduces Procedural Artificial Narrative using Generative AI (PANGeA), a structured approach that leverages large language models (LLMs) for generating narrative content in turn-based role-playing video games. Unlike prior applications of LLMs, PANGeA not only generates game level data but also fosters dynamic interactions between the player and environment that align with the procedural game narrative. The system uses a novel validation system to evaluate text input and generate responses that align with the unfolding narrative. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary PANGeA is a new way to use computers to create stories for video games. It helps designers make more exciting and interactive games by using special computer programs called large language models. These models can understand and respond to human language, like you and me talking! PANGeA makes sure the computer’s responses fit with the game’s story, so it feels like a real adventure. |
