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Record W2003082482 · doi:10.1109/tase.2011.2163510

Workflow Nets for Multiagent Cooperation

2011· article· en· W2003082482 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Automation Science and Engineering · 2011
Typearticle
Languageen
FieldComputer Science
TopicPetri Nets in System Modeling
Canadian institutionsWestern University
Fundersnot available
KeywordsSoundnessPetri netReachabilityWorkflowComputer scienceConcurrencyDistributed computingTask (project management)Process architectureTheoretical computer scienceProtocol (science)Programming languageExtension (predicate logic)Software engineeringDatabaseSystems engineeringEngineering

Abstract

fetched live from OpenAlex

We present a formal framework for robotic cooperation in which we use an extension to Petri nets, known as workflow nets, to establish a protocol among mobile agents based on the task coverage they maintain. Our choice is motivated by the fact that Petri nets handle concurrency and that goal reachability, or soundness, can be theoretically established. In particular, we define a mathematical cooperation operator which turns cooperation problems expressed as workflow nets into algebraic representations. While we do not address the problem of efficiency, we formally demonstrate that this framework guarantees soundness, or goal reachability, using workflow nets.

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.

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: Methods · Consensus signal: none
Teacher disagreement score0.803
Threshold uncertainty score0.382

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 communication0.0000.001
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 head0.041
GPT teacher head0.247
Teacher spread0.206 · 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