Tree narrative and AI interaction: Optimization and narrative bias handling prospects
This paper reviews the current research on interactive narratives, particularly the tree narrative structure, analyzing the methods of player-AI interaction, the design of narrative branches, and the mechanisms by which player decisions influence the story's progression. It explores the definitions, classifications, and applications of tree narratives in gaming, emphasizing the significance of player-AI interaction and its impact on narrative outcomes. The study identifies and analyzes potential narrative deviations resulting from player-AI interactions within tree structures and introduces an AI-assisted automatic scoring system based on hypothesis testing and Bayesian analysis to effectively identify narrative biases.
Authors
- Yifeng Bi
Institutions
- Anhui University (CN)
- Stony Brook University (US)
Publication Details
- Journal
- Applied and Computational Engineering
- Published
- 2024-09-10
- DOI
- https://doi.org/10.54254/2755-2721/71/20241616
- Primary Topic
- Computational and Text Analysis Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00