Increasing Population (μ + λ)-CMA-ES with Centre and Elitism (IPOP!+)
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
Elitism has previously been introduced to the CMA-ES family of algorithms, where the “’,’ selection operator is replaced by the “+” selection operator. Here we investigate in detailed the addition of elitism to IPOP. Furthermore, a new selection operator was added: the “!” operator (pronounced “bang” or “here”). This operator includes the results of ES recombination into the population for selection, unmodified by mutation, and evaluated separately. From the analysis, we noticed a remarkable improvement in the behavior of IPOP with or without elitism. Only one function (Levy) proved difficult when elitism was used. Under close examination, it was determined that for this function, the population under elitism converges prematurely, and stalled out. Currently we do not know what is the cause of this difference. Perhaps in the future this effect could be avoided or detected and remedial measures applied.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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