A Spatial Partitioning Based Crowd Evacuation Model
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 paper studies a large population evacuation model within the linear quadratic mean field games framework. The evacuation time horizon is fixed, and space is subdivided into regions. Depending on its initial position with respect to the specified regions, each agent has a limited selection of possible exit choices. Agents’ motions are affected by their respective regional cohorts’ positions mean. Regions interact through their shared exits’ flows which creates an inter-regional network effect. A sufficient upper bound on the time horizon is derived to guarantee that finite escape time behavior is avoided. Besides, existence of an infinite population based Nash equilibrium is established. Finally, we illustrate, through simulations, the model’s behavior for given agents’ initial distributions and exits arrangement setups.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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