Adapting environment-mediated self-organizing emergent systems by exception rules
Why this work is in the frame
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Bibliographic record
Abstract
Due to the absence of global knowledge, elements in a self-organizing emergent system tend to make suboptimal local decisions that result in globally inefficient solutions. However, improving the solutions of such systems, which work in a bottom-up style, by the principles of self-adaptive systems, which work in a top-down style, is not a straight forward process. In this paper, we present challenges and constraints that have to be respected during this process and describe early work on an approach, how to autonomously adapt the local behavior of self-organizing elements by so-called exception rules in order to improve the performance of the global solution. In particular, we present a set of exception rules that can be employed in different situations for the improvement of environment-mediated, self-organizing emergent solutions to pickup and delivery problems.
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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) | 0.001 | 0.001 |
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