A Distributed Guided Genetic Algorithm for Max-CSPs
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.
Bibliographic record
Abstract
Ce papier traite les problemes de satisfaction maximale des contraintes (Max-CSP) connus pour leur aspect NP-Complet, et ce, par une approche Multiagent (MA) des algorithmes genetiques (AGs) qui sont qualifies de couteux en termes de temps. L'objectif est donc double: d'une part, tirer profit de l'efficacite des AGs pour donner une bonne qualite aux Max-CSPs et, d'autre part, beneficier des fondements MA afin de reduire la complexite temporelle des AGs. Les agents, crees dynamiquement, cooperent pour satisfaire le maximum de contraintes. Chaque agent s'occupe d'une sous-population de chromosomes violant le meme nombre de contraintes, et ce, a l'aide d'un AG guide par le concept de template et l'heuristique de minimisation de conflits. Pour montrer l'avantage de cette approche des comparaisons experimentales avec une version centralisee sont presentees.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it