Multi-decision decentralized control of discrete event systems : Application to the C&P architecture
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 article deals with decentralized supervisory control, where a set of supervisors cooperate in order to control a plant. We propose a new control framework where each supervisor issues a tuple of so called micro-decisions, instead of a single decision for a controllable event. The proposed approach is called multi-decision supervisory control and is intended to be applicable to any existing decentralized architecture in order to generalize the latter. In this paper, we demonstrate the applicability of the new framework to the conjunctive and permissive (C&P) architecture. The obtained architecture is naturally called C&P multidecision architecture. We define and study the notion of C&P m-coobservability, which is useful to characterize the class of achievable languages. Since C&P m-coobservability seems to be undecidable, we finally propose a stronger and obviously decidable version of C&P m-coobservability.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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