Three-Dimensional Agent-Based Model and Simulation of a Burglar's Target Selection
Bibliographic record
Abstract
Residential burglary has been one of the most active research topics in the study of crime. It is also one of the most common crime types and sometimes has a long-lasting impact on victims not only financially but also psychologically. In order to understand residential burglary, many methods have been used such as analyses of crime data and national crime survey data, interviews with incarcerated burglars (and active ones), and developing models and simulations. Recently agent-based modeling and simulation (ABMS) has widely become utilized to understand burglars' behaviours at an individual level. However, many studies have developed and simulated their burglar models and environments in two dimensions (2D). This paper presents realistic, three-dimensional (3D) models and simulations of a residential burglar and its virtual environment. By incorporating 3D aspects of the models and simulations, accurate microinteractions between the burglar and its environment can be simulated. The presented burglar model shows its target selection process based on wealth and layout cues. The benefits and limitations of the 3D ABMS approach are discussed. A few case studies show the validity of this approach and the possibility of its predictive and preventive use.
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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".