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Record W2071262178 · doi:10.1109/cdc.2012.6425842

A bounded connectivity preserving aggregation strategy with collision avoidance property for single-integrator agents

2012· article· en· W2071262178 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
TopicDistributed Control Multi-Agent Systems
Canadian institutionsConcordia University
Fundersnot available
KeywordsBounded functionIntegratorCollision avoidanceComputer scienceController (irrigation)Control theory (sociology)Property (philosophy)Range (aeronautics)Limit (mathematics)Regular polygonCollisionSet (abstract data type)Multi-agent systemDouble integratorAggregate (composite)Mathematical optimizationMathematicsControl (management)EngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

This paper presents a potential-based bounded distributed connectivity preserving control strategy for aggregation of a set of single-integrator agents. Under the proposed control strategy, if two agents are in the connectivity range at some point in time, they will stay connected thereafter. Under the proposed controller, the agents finally aggregate while avoiding collision in such a way that the average of the distances between every pair of neighboring agents is bounded by a pre-specified positive real number, which can be chosen sufficiently small. The results are developed based on some important characteristics of the positive limit set of the closed loop system under the proposed control strategy and a fundamental property of convex real functions. The theoretical results are verified by simulation.

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: Empirical · Consensus signal: none
Teacher disagreement score0.884
Threshold uncertainty score0.588

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 communication0.0000.002
Open science0.0010.000
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 head0.051
GPT teacher head0.269
Teacher spread0.218 · 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

Citations5
Published2012
Admission routes1
Has abstractyes

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