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Record W1979004417 · doi:10.1142/s0219198900000081

EVOLUTIONARY AND DYNAMIC STABILITY IN SYMMETRIC EVOLUTIONARY GAMES WITH TWO INDEPENDENT DECISIONS

2000· article· en· W1979004417 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

VenueInternational Game Theory Review · 2000
Typearticle
Languageen
FieldDecision Sciences
TopicGame Theory and Applications
Canadian institutionsUniversity of CalgaryWilfrid Laurier University
Fundersnot available
KeywordsMathematical economicsStability (learning theory)Stochastic gameNash equilibriumStatement (logic)Competition (biology)Evolutionarily stable strategyRisk dominanceBest responseEpsilon-equilibriumMathematicsEconomicsGame theoryComputer scienceEcologyBiologyMachine learning

Abstract

fetched live from OpenAlex

A two-decision competition model is developed where players may choose different strategies at different decisions knowing that their payoff at one decision is not affected by their performance at the other. It is shown that both static solution concepts of Nash and evolutionarily stable equilibria for the two-decision model are directly related to those of the separate decisions. Furthermore, if there are at most two pure strategies at each decision, dynamic stability can also be characterised through a separate analysis of each decision. However, when there are more than two strategies, this last statement is not always true.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.001

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 head0.057
GPT teacher head0.376
Teacher spread0.320 · 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