Virtual Character Behavior Architecture using Cyclic Scheduling
Why this work is in the frame
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Bibliographic record
Abstract
A story-based video game contains many characters. The majority are virtual characters controlled by artificial intelligence. In recent years, virtual character artificial intelligence has developed slower than other aspects of video games, such as graphics, mainly due to the cost of scripting complex and believable virtual characters. To tackle this bottleneck in content creation, this research proposes a new Tiered Behavior Architecture model for controlling the behaviors of virtual characters. For local scenes, techniques such as Behavior Capture with Hidden Markov Models, which has been evaluated by user studies that validated its success in generating fine-grained behaviors, can be used to fulfill the roles. At a larger scale, a hierarchical cyclic scheduler determines the general circumstances, schedules, and objectives of the virtual characters as well as the roles that will accomplish these objectives. This paper describes experiments and user studies that validate this model.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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