Comments on “Feedback Control Logic for Forbidden-State Problems of Marked Graphs: Application to a Real Manufacturing System”
Bibliographic record
Abstract
The AIP manufacturing testbed discussed by Ghaffari et al. (see ibid., vol. 48, p.18-29, 2003) was previously treated using automaton-based [as distinct from Petri net (PN)-based] supervisory control theory (SCT). Problems of this general type have been transcribed from the PN literature, sometimes greatly enlarged, converted into SCT format, and solved using integer-decision-diagram (IDD) techniques with only modest expenditure of time and memory. Thus it is substantially misleading to state, that "the AIP control problem would require huge processing time and memory if addressed with the Ramadge-Wonham [SCT] approach." In contrast to the restriction in Ghaffari et al. (2003) to "marked graphs", no prior structural restrictions other than finiteness of the state set (or boundedness in the case of PNs) were placed on the models of system components.
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.
How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".