Weak Invariant Simulation and Its Application to Analysis of Parameterized Networks
Why this work is in the frame
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Bibliographic record
Abstract
Multi-process networks figure in many engineering applications. Parameterized discrete event systems provide a convenient means of modeling such networks when the number of subprocesses is arbitrary, unknown or time-varying. Unfortunately, some key properties of these networks, such as nonblocking and deadlock-freedom, are undecidable. Moreover, mathematical tools supporting analysis of these networks are limited. This paper introduces a novel mathematical notion, weak invariant simulation, which is adapted to the analysis of synchronous products of discrete event systems. Furthermore, it proposes an efficient method to check whether a finite-state generator weakly invariantly simulates another finite-state generator with respect to a specific subalphabet. This new simulation relation is used to define a tractable subclass of parameterized ring networks of isomorphic subprocesses in which deadlock-freedom is decidable. Within this framework, a procedure is given to determine the reachable deadlocked states of the network. The effectiveness of the procedure is demonstrated by the deadlock analysis of a version of the dining philosophers problem.
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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 | 0.001 | 0.001 |
| 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