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
This chapter provides a brief overview of those virtual agent implementations directly inspired by the cognitive architecture: Soar. This chapter will take a qualitative approach to discussing examples of virtual Soar-agents. Finally, this chapter will speculate on the future of Soar virtual characters. The goals of this chapter are sixfold. The first goal is to explain why cognitive architectures are becoming increasingly important to virtual agent design(s). The second goal is to convey why this chapter focuses exclusively on virtual agents that utilize the Soar architecture. The third goal is to explore some of Soar's technical details. The fourth goal is to showcase a few diverse examples where Soar is beginning to have a design impact on virtual agents. The fifth goal addresses Soar's limitations – when applied to agent design in virtual environments. The final goal speculates on ways Soar can be expanded for virtual agent design(s) in the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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