Invariant weak simulation and analysis of parameterized networks
Bibliographic record
Abstract
Communicating multi-process networks appear in many real-life applications. Parameterized discrete event systems provide a convenient way of modeling these networks. Unfortunately, some key problems such as checking solvability of the nonblocking synthesis problem and checking satisfaction of a temporal property in parameterized networks are undecidable. In this paper, we consider parameterized ring networks and introduce a new framework for blocking analysis of such networks. To render the blocking analysis tractable, we restrict the interactions between processes. The structural assumptions are formulated in terms of a new mathematical relation: invariant weak simulation of one process by another. Our assumptions serve to ensure that while both immediate neighbors may prevent a process from executing shared events, only one neighbor can permanently prevent an event from occurring; in that sense, control only flows around the ring in one direction. We prove that our assumptions have this desired result. The effectiveness of the proposed framework is demonstrated by analysis of a version of the dining philosophers problem.
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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 | 0.001 |
| 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 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".