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Record W4313452114 · doi:10.21203/rs.3.rs-2396073/v1

Robust Sequential Stopping Games

2023· preprint· en· W4313452114 on OpenAlexaff
Israel Igietsemhe, Chi-Guhn Lee

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldHealth Professions
TopicHealthcare Operations and Scheduling Optimization
Canadian institutionsThe King's UniversityCanada Research ChairsUniversity of Toronto
Fundersnot available
KeywordsStochastic gameRepeated gameConsistency (knowledge bases)Sequential gameOptimal stoppingComputer scienceStopping timeMathematical economicsProcess (computing)Screening gameValue (mathematics)Normal-form gameMathematicsMathematical optimizationGame theoryArtificial intelligenceStatisticsMachine learning

Abstract

fetched live from OpenAlex

Abstract We study the robust equilibrium for sequential stopping games to give the conditions under which the game’s values exist. Three scenarios of the game are analyzed. G1 is the game where only the maximizing player optimizes in a worst-case scenario and G2 is the game where only the minimizing player optimizes in a worst-case scenario.We show that under the conditions of integrability and time consistency, the game value exists for robust zero-sum two-person sequential stopping games (G1, G2) when the payoff process is an ambiguous adapted process under multiple probability measures. We also establish the relationship between G1 and G2. MSC Classification: 62L15 , 91A15

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.590
GPT teacher head0.592
Teacher spread0.002 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2023
Admission routes1
Has abstractyes

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