A discrete representation for real optimization with unique search properties
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
Walking triangle representations for real optimization are linear representations drawn from the group that acts on simplices of Euclidean space. The representation encodes a series of modifications to an initial simplex, evaluating the quality of the point at its center of mass for the function being optimized. Different operations available in the representation permits easy tailoring of the degree of exploration and exploitation implemented and also permit control over the order in which they happen. Some operations perform search with linear differences in the position of the search point while others exponentially increase or decrease the distance between adjacent points. The current work focuses on developing theory and experimentally testing a walking triangle representation based on the walk, center, and uncenter moves representing changes in the position of the modeled point that are linear, exponentially decreasing, and exponentially increasing, respectively. The experimental results are compared with one another and with a standard evolutionary algorithm. A new test function called the eight hill function, specifically intended to test the ability of an algorithm to explore, is presented.
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.
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 | 0.000 | 0.001 |
| 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