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Record W3163640945 · doi:10.1145/1082983.1082978

A layered architecture for real-time distributed multi-agent systems

2005· article· en· W3163640945 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

VenueACM SIGSOFT Software Engineering Notes · 2005
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsDistributed computingComputer scienceComputationArchitectureResource (disambiguation)Quality of serviceService (business)Computer network

Abstract

fetched live from OpenAlex

Real-time computations in open distributed systems have functional as well as coordination requirements. Specifically, distributed agents may require to be coordinated to satisfy real-time and other quality of service (QoS) constraints. However, this coordination is difficult to achieve because of the unpredictability of computational resource availability in an open system.A three-layered architecture for computations in an open distributed multi-agent system is presented, which keeps functional, coordination and resource concerns of an application separate, allowing each to be studied separately. Functional requirements of the computation are pursued by a system of primitive agents called actors. Timing constraints are imposed on these agents through meta-operations carried out by coordinators. Resource encapsulations called cyberorgs are used for creating execution environments for agents and coordinators with predictable availability of resources.Programming constructs are developed for implementing cyber-orgs and coordinators.

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)0.133
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.283
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.133
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.035
GPT teacher head0.279
Teacher spread0.243 · 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