Facilitating player progression by implementing procedural music in videogames
Bibliographic record
Abstract
While the multi-million-dollar videogame industry sees constant improvements in visuals and processing power with every new processor, gaming console, or graphics card release, is there any avenue to pursue new innovations in this discipline? One answer lies in the introduction of procedural music in videogames as an innovative means of overcoming the repetitive nature of traditionally composed game music and to enhance the immersive response of game music to player actions. While most studies are preoccupied with the descriptive evaluation of how entertaining procedural music is in comparison to traditionally composed music, we pursue a novel study on the utility of implementing procedural music in videogames as a tool for facilitating player progression. To do so we employ objective, quantitative measures to gather results that can quantify the utility of implementing procedural videogame music, unlike other studies. We demonstrate that users playing a game with a procedural music model that actively instructs and assists players can complete game levels in a significantly more time efficient manner and are more likely to rate the procedural music model as having significantly contributed to the game's entertainment and engagement.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".