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Record W2088998139 · doi:10.1109/acc.2012.6314999

Invariant weak simulation and analysis of parameterized networks

2012· article· en· W2088998139 on OpenAlexaff
M. H. Zibaeenejad, J.G. Thistle

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicPetri Nets in System Modeling
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsParameterized complexityUndecidable problemComputer scienceInvariant (physics)Theoretical computer scienceBlocking (statistics)Model checkingProcess (computing)Distributed computingAlgorithmMathematicsProgramming languageDecidabilityComputer network

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.818
Threshold uncertainty score0.203

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.043
GPT teacher head0.288
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2012
Admission routes1
Has abstractyes

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