Analysis of ReGEN as a Graph-Rewriting System for Quest Generation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Using procedural narrative generation in video games provides a flexible way to extend game play and provide more depth to the game world at low cost to the developers. Current examples of narrative generation in commercial games, however, tend to be simplistic, resulting in repetitive and uninteresting stories. In this paper, we develop a system for narrative generation using a context-aware graph-rewriting framework. We use a graph representation of the game world to create narratives which reflect and modify the current world state. Using a novel set of metrics to evaluate narrative quality, we validate our approach by comparing our generated narratives to other procedurally generated stories, as well as to authored narratives from commercially successful and critically praised games. The results show that our narratives compare favorably to the authored narratives. Our metrics provide a new approach to narrative analysis, and our system provides a unique and practical approach to story generation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it