Toward an estimation of distribution algorithm for the evolution of artificial neural networks
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
This paper presents the preliminary results of a unique method of neuroevolution called Probabilistic Developmental Neuroevolution (PDNE). PDNE builds upon Gene Expression Programming (GEP) and Probabilistic Incremental Program Evolution (PIPE). Instead of building a Probabilistic Prototype Tree, as in PIPE, a Probabilistic Prototype Chromosome is built. The chromosome has a similar structure to a GEP chromosome (head, tail, and weight domain) and contains probabilities for each element of the gene. With this methodology, neural networks can be expressed in a similar manner to GEP, and solutions can be evolved via an Estimation of Distribution Algorithm. Preliminary results show promise, but further work is required to match the results of GEP.
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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