Cournot game with incomplete information based on rank-dependent utility theory under a fuzzy environment
Bibliographic record
Abstract
In most existing literatures on Cournot game, game behaviour between players is based on the hypothesis that people are complete rationality. However, players’ decisions are often affected by their behavioural characteristic and psychology preference. Traditional Cournot model also doesn’t deal with ambiguous information. Based on rank-dependent utility theory, this paper develops an incomplete information Cournot game in an ambiguous decision environment, where the form of ambiguity is described by a set of fuzzy parameters, and behavioural pattern is reflected by means of emotional function in rank-dependent utility. Further, we investigate the Nash equilibrium quantity of each manufacture in this kind of fuzzy Cournot game with incomplete information. Finally, the proposed Cournot model is applied to a case study, and dynamic variation and sensitivity analysis of optimal quantity with respect to decision-maker’s behaviour pattern are discussed in detailed, which illustrates that the proposed Cournot model is more reasonable than traditional Cournot model.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".