Real‐time optimization of dynamic systems using multiple units
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
Abstract Model‐free, unconstrained, real‐time optimization of the operating point of a dynamic system involves forcing the gradient of the cost function to zero. In these methods, gradient estimation is a key issue, for which methods that perturb the input over time are used. The main limitation of these methods is that they require the dynamics of the adaptation to be two orders of magnitude slower than the system dynamics. To circumvent this limitation, a novel, simple, yet effective way of estimating the gradient is presented in this paper. Multiple identical units with non‐identical inputs are used and the gradient is computed via finite difference. Thus, the perturbation is along the ‘unit dimension’, thereby allowing a faster adaptation. The convergence of the scheme is rigorously established via Lyapunov analysis. An illustrative example is provided where the proposed scheme resulted in an 100‐fold improvement in the time needed for convergence. Copyright © 2007 John Wiley & Sons, Ltd.
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 | 0.000 |
| 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