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Record W2144260073 · doi:10.1109/acc.2007.4282637

Multi-UAV Decentralized Task Allocation with Intermittent Communications: the DTC algorithm

2007· article· en· W2144260073 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

VenueProceedings of the ... American Control Conference/Proceedings of the American Control Conference · 2007
Typearticle
Languageen
FieldComputer Science
TopicDistributed Control Multi-Agent Systems
Canadian institutionsMcGill UniversityDefence Research and Development CanadaLockheed Martin (Canada)
Fundersnot available
KeywordsAsynchronous communicationTask (project management)Computer scienceNonlinear systemTask analysisAlgorithm designDistributed computingAlgorithmComputer networkEngineering

Abstract

fetched live from OpenAlex

A new decentralized task allocation algorithm for UAVs using intermittent and asynchronous communications is presented. The proposed algorithm fosters a decentralized task consensus (DTC) across the UAVs. To increase the efficiency of the communications, the decision to communicate is based on the outputs of the task allocation procedure. Simulation results with a realistic nonlinear model of almost-lighter-than-air-vehicles are presented. Compared with a decentralized information consensus (DIC) algorithm, the DTC algorithm is demonstrated to require less communications to achieve a similar or better cooperative behavior.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.527
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.003
Science and technology studies0.0010.006
Scholarly communication0.0010.001
Open science0.0160.002
Research integrity0.0000.001
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 head0.018
GPT teacher head0.255
Teacher spread0.237 · 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