Agent-Based Behavioral Model and Simulation of Fire Egress
Bibliographic record
Abstract
Disastrous fires can cause death, injuries, and property damage. In certain cases, mass evacuations of buildings are also required to ensure safety. Building fires are particularly dangerous because of added factors such as confinement and height of buildings. Fire egress is essential to fire safety in buildings. Evaluating such safety is not easy since simulating fire egress with real subjects (and possibly with a real fire or smoke) poses ethical issues. There have been computer simulations of fire egress. However, current evacuee models are too simple and do not reflect the behavior of actual evacuees. This paper presents a comprehensive behavioral model and simulation of evacuees in a building fire. The fire egress simulation system is based on the behavioral model that is verified using simulation experiments. This simulation system can be used to evaluate the fire egress in actual buildings and can assist in determining fire safety standards. Simulation results are presented and future research is discussed.
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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 | 0.000 | 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 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".