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Record W4249396061 · doi:10.3233/fi-2009-156

Swarm Intelligence

2009· article· en· W4249396061 on OpenAlexfundno aff

Bibliographic record

VenueFundamenta Informaticae · 2009
Typearticle
Languageen
FieldEngineering
TopicSlime Mold and Myxomycetes Research
Canadian institutionsnot available
FundersCanadian Arthritis NetworkNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsSwarm behaviourSwarm intelligenceComputer scienceArtificial intelligenceMachine learningParticle swarm optimization

Abstract

fetched live from OpenAlex

This volume of Fundamenta Informaticae (FI) contains papers for a special issue on swarm intelligence as well as regular papers contributed to FI.Swarm Intelligence is an innovative distributed intelligent paradigm for solving optimization problems, which is originally inspired from the biological examples by swarming, flocking and herding phenomena in vertebrates.In the literature, it possible to locate different variants of Swarm Intelligence paradigms.The most popular paradigms are Particle Swarm Optimization (PSO), which incorporates swarming behaviors observed in flocks of birds, schools of fish, or swarms of bees and the Ant Colony Optimization (ACO) algorithm inspired by the foraging behaviour of real ants.This volume contains articles introducing advances in the foundations and applications of swarm intelligence.These advances have significant implications in a number of research areas such as constrained optimization problems, fast corner detection in gray-level images, harmony search algorithm, measuring resemblances between swarm behaviours, multiple-objective flexible job-shop scheduling, object tracking, and particle swarm optimization.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.906
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.002

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 head0.013
GPT teacher head0.248
Teacher spread0.235 · 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 designOther design
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

Citations0
Published2009
Admission routes1
Has abstractyes

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