Press A or Wave: User Expectations for NPC Interactions and Nonverbal Behaviour in Virtual Reality
Bibliographic record
Abstract
Non-playable characters (NPCs) are important in games, as they can provide guidance to the player, create social engagement, and advance the game's narrative. Although much research exists regarding NPC interactions for traditional gaming environments, e.g. desktop or console, fewer works have considered this from a virtual reality (VR) perspective. Our work first uncovers the salient and unique dimensions of VR NPC interactions through observations of 47 existing games. We find that VR NPC interactions have an extended set of interaction mechanisms due to two key factors - interaction triggers and player constraints within the game, driven by the unique qualities of physical motion and immersion afforded by the medium. We augment these findings through a user study performed on 18 participants in a VR environment. Participant interactions with a responsive NPC allow us to delve deeper into understanding player perception and expectations of NPC behaviour and interactions. Our findings outline player expectations for NPC realism, player agency during NPC interaction, and NPC expected behaviour and feedback. We tie our findings into discussions on player agency within VR, highlighting design suggestions to develop NPCs to better fit within social behaviour expectations.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| 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".