Supervisory control of dense real-time discrete-event systems with partial observation
Why this work is in the frame
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Bibliographic record
Abstract
In supervisory control theory, the basic task of the supervisor is to disable certain events of the plant so that the obtained behaviour lies within a given specification. We propose a method which extends this theory with the following two points. First, the plant and the specification contain temporal constraints and are described by a model called Timed Automata (TA). Second, the supervisor has only a partial observation of the behaviour of the plant. The problem that arises with the TA model is that the state space can be infinite. Recently, we proposed a method to finitely represent the state space which generates less states than the well-known region graph approach. Its principle consists of transforming a TA into a Finite State Automaton (FSA) using two special types of events: Set and Exp. Such a FSA is denoted se-FSA. In this article, we propose a method for the supervisory control of timed discrete event systems that are modelled by TA and partially observable. We use the above-mentioned transformation procedure for representing the plant and the specification by two se-FSAs. Then, we develop a procedure for generating the supervisor from the two se-FSAs that represent the plant and the specification. We also propose a supervisory control architecture.
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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