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Record W1981467987 · doi:10.1145/1878537.1878696

UAV search strategies using Cell-DEVS

2010· article· en· W1981467987 on OpenAlexaff
Keith Holman, Jeremy Kuzub, Gabriel Wainer

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
TopicSimulation Techniques and Applications
Canadian institutionsCarleton University
Fundersnot available
KeywordsDEVSComputer scienceRotation formalisms in three dimensionsFormalism (music)Discrete event simulationModeling and simulationArtificial intelligenceData miningTheoretical computer scienceDistributed computingReal-time computingSimulationMathematics

Abstract

fetched live from OpenAlex

Cell-DEVS is an extension to the DEVS formalism that allows the definition of cellular models. CD++ is a modeling and simulation tool that implements Discrete Event Simulation (DEVS) and Cell-DEVS formalisms. The methodology proposed in this paper uses the Cell-DEVS formalism and C++ tool chain [4, 5] to model Uninhabited Aerial Vehicle (UAV) search in a dynamic intelligence environment. Algorithms proposed in previous works [1] were applied to modify the intelligence environment over time. The UAV search pattern was based on this information and the resulting simulation demonstrates emergent UAV search patterns in this intelligence environment. Rule sets model the degradation of this intelligence over time using algorithms proposed in [1], are referred to as a diffusion algorithm; the UAV traversed this map using a hill-climbing algorithm. The resulting UAV search pattern showed preference for the local maximum of target location probability before total maximum to produce an intuitive search pattern. The Cell-DEVS architecture and CD++ tool chain provided a robust development and visualization environment suited to this research.

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.

How this classification was reachedexpand

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.252
Threshold uncertainty score0.997

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)0.0040.000

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 head0.263
GPT teacher head0.515
Teacher spread0.253 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2010
Admission routes1
Has abstractyes

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