ANC Analytical Payoff Functions for Networks with Endogenous Bilateral Long Cheap Talk
Bibliographic record
Abstract
We derive an almost non cooperative (ANC) analytical payoff function for all three-agent Aumann-Myerson (1988) games, and tractable ones exist for all three-agent A-M-like network games with any fixed valuation, in contrast to restricted results in the literature, if at all. Unlike link proposal game A-M and Myerson (1986), ANC has dynamic bilateral cooperation as we assume bilateral long cheap talk among three agents (differing from A-Hart (2003)), i.e., (1) pairs "smooth" Nash bargain during link discussions over credible expected payoffs induced by equilibria of a Nash demand-like game-where a link forms if the two agents match (2) double proposals, i.e., payoffs that sum up to their Myerson values in the prospective graph, and future bilateral coordination schemes. Thus, payoffs in the final graph of ANC yield a "variable Myerson value pair" which accounts for future possibilities of link formation. Instead, A-M has (a) "fixed" Myerson values (1977). In ANC, key (b) multiple equilibria in A-M-with conflicting requests of two agents to an indifferent third one-are solved, as coordination on requests by earlier linked pairs prevails if credible. This follows from (3) almost assuming that schemes are reminded chronologically "behind closed doors" as there is almost a natural first-mover advantage. (c) Inefficiency is possible in A-M, but not in ANC. We state some of the complete analytics for A-M. Also, in strictly superadditive games, only two-link graphs form. If only a link-coalition of two-forms then they achieve the grand coalition's worth
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".