Efficient implementation of fairness in discrete-event systems using queues
Why this work is in the frame
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Bibliographic record
Abstract
Fair synthesis of supervisory control for discrete-event systems is discussed. It is argued that a least restrictive supervisor does not in general exist unless a bound is placed on the number of transitions before which a desired event is required to happen. It is shown how such bounded fairness can be implemented using first-input-first-output (FIFO) queues. Although the language generated by a queue is not the largest among bounded fair restrictions of a behavior, nonoptimality can be exploited in hierarchical implementation of queues by grouping a subset of subsystems as a team and designing two modular queues: one to implement fairness locally among the team members, and the other to implement fairness globally between the team and other subsystems.
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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 | 0.001 | 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