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Record W2119064581

The optimal searcher path problem with a visibility criterion in discrete time and space

2009· article· en· W2119064581 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicOptimization and Search Problems
Canadian institutionsDefence Research and Development CanadaUniversité Laval
Fundersnot available
KeywordsMathematical optimizationPath (computing)VisibilityDiscretizationMotion planningAny-angle path planningComputer scienceGridObject (grammar)Integer programmingMathematicsAlgorithmTopology (electrical circuits)Artificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

Abstract – In this paper, the problem of path planning for a ground search unit looking for an object of unknown location is considered. As in the classical optimal searcher path problem, the probability of finding the search object is the main criterion of optimality and the search unit is constrained by the environment topology that influences its choices for a navigable path as well as its detection capabilities. This paper proposes an extension to the classical optimal searcher path problem in discrete time and space by integrating inter-region visibility as an additional criterion. This new formulation allows a refinement in the discretization of the space in which a ground search unit evolves. A general mixed-integer programming model is proposed, and experimental results with a moving object in grid environments are discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.949
Threshold uncertainty score0.364

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.257
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations14
Published2009
Admission routes1
Has abstractyes

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