An Exploration-only Exploitation-only Hybrid for Large Scale Global Optimization
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
Two factors affect the effectiveness of exploration, the bias introduced by selection and the concurrence of exploration and exploitation. The Leaders and Followers metaheuristic was designed to reduce the bias from selection by using a two-population scheme. Minimum Population Search was designed to limit the concurrence of exploration and exploitation through the use of Thresheld Convergence in its sampling strategy. This paper presents Unbiased Exploratory Search, which combines both approaches and simultaneously addresses the effects of these two factors. An exploration-only exploitation-only hybrid is then presented using Unbiased Exploratory Search for the exploration-only phase of the hybrid. The hybrid is tested on the CEC large scale optimization benchmark.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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