SEARCHING A POLYGONAL REGION FROM THE BOUNDARY
Bibliographic record
Abstract
Polygon search is the problem of finding mobile intruders who move unpredictably in a polygonal region, using one or more mobile searchers. Different levels of vision are assumed to model the ability of the searchers. In this paper we mainly consider a special case of this problem, termed boundary search, in which a single searcher has to find the intruders from the boundary of the region. Our main result is that a single searcher whose vision is limited to the ray of a single flashlight is just as capable as a single searcher having a light bulb that gives 360° vision, that is, any polygon that can be searched by the latter from the boundary can also be searched by the former from the boundary. The proof of the equivalence uses another new result, termed Monotonic Extension Theorem, together with a two-dimensional diagram called the planar boundary visibility map that represents the status of the search as a function of time. We partially settle a long-standing conjecture on the equivalence of the abilities of two types of searchers, one having two flashlights and the other having full 360° vision, for the general (non-boundary) polygon search problem.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".