Decentralized modular control of concurrent Fuzzy Discrete Event Systems
Bibliographic record
Abstract
In order to analyze the event driven complex systems with uncertainties in their events and state transitions, Fuzzy Discrete Event Systems (FDES) has been proposed as an extension to the formal Discrete Event Systems theory (DES). In this paper we investigate the decentralized modular supervisory control problem of FDES with partial observation for systems which are composed of concurrently operating, multiple interacting modules with uncertainties in their events and states. The modular decentralized fuzzy supervisor consists of set of local fuzzy supervisors, one for each module and each with its own sensing and acting capabilities. Moreover, the communication is not allowed between the local fuzzy supervisors. The notion of separability for fuzzy languages is introduced and the property of a fuzzy language specification which is called separably - controllable - observable that is required for verifying the existence of modular fuzzy supervisors is defined. Some examples are presented to realize the theoretical developments.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".