Design Techniques for Planning Navigational Systems in 3-D Video Games
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
Navigation is an essential element of many high-budget games (known as AAA titles). In such products, players are expected to walk through and interact with aesthetically rich 3-D spaces. Therefore, designers should provide meaningful information to guide the users within a challenging environment. While there has been much research on both games and 3-D environments, there is very little research investigating design techniques used to guide players through 3-D game worlds. This paper is focused on proposing a set of navigational patterns or techniques currently used in commercial 3-D action-adventure titles. These design techniques are composed of [a] 21 patterns used to aid navigation, [b] three level design choices affecting navigation, and [c] eight game mechanics related to navigation. We uncovered these design techniques through a detailed analysis of 21 3-D action-adventure games. This contribution has several important facets. First, the set of design techniques and terminology proposed here can be used as a training construct to teach 3-D game and environment design. Second, it can also be used as a toolset for designers. Third, it will provide an important start for a formal vocabulary that can be used by designers and researchers discussing navigation in 3-D games.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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