Evaluating strategies for running from the cops
Why this work is in the frame
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Bibliographic record
Abstract
Moving target search (MTS) or the game of cops and robbers has a broad field of application reaching from law enforcement to computer games.Within the recent years research has focused on computing move policies for one or multiple pursuers (cops).The present work motivates to extend this perspective to both sides, thus developing algorithms for the target (robber).We investigate the game with perfect information for both players and propose two new methods, named TrailMax and Dynamic Abstract Trailmax, to compute move policies for the target.Experiments are conducted by simulating games on 20 maps of the commercial computer game Baldur's Gate and measuring survival time and computational complexity.We test seven algorithms: Cover, Dynamic Abstract Minimax, minimax, hill climbing with distance heuristic, a random beacon algorithm, TrailMax and DA-TrailMax.Analysis shows that our methods outperform all the other algorithms in quality, achieving up to 98% optimality, while meeting modern computer game computation time constraints.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 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