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Record W2099823045 · doi:10.1109/cdc.2005.1583007

An Extension of Duality and Hierarchical Decomposition to a Game-Theoretic Framework

2006· article· en· W2099823045 on OpenAlex
Lacra Pavel

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

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAdvanced Queuing Theory Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNash equilibriumGame theoryDuality (order theory)Mathematical optimizationNormal-form gameBest responseMathematical economicsEquivalence (formal languages)Extension (predicate logic)Computer scienceDecompositionOptimization problemMathematicsRepeated gameDiscrete mathematics

Abstract

fetched live from OpenAlex

This paper extends some duality results from a standard optimization setup to a noncooperative (Nash) game framework. A coupled constrained Nash game is considered. Solving directly such a coupled Nash game requires coordination among possibly all players. An alternative approach is proposed based on the equivalence to a special constrained optimization problem for an NG-game cost function. By exploiting specific separability properties of the NG-game cost, this duality approach leads to a natural hierarchical decomposition into a lower-level uncoupled Nash game and a higher-level system optimization 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.

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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score0.349

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.008
GPT teacher head0.275
Teacher spread0.267 · 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

Quick stats

Citations5
Published2006
Admission routes1
Has abstractyes

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