Impact of Asynchrony on the Behavior of Rational Selfish Agents
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.
Bibliographic record
Abstract
The behavior of rational selfish agents has been classically studied in the framework of strategic games in which each player has a set of possible actions, players choose actions simultaneously and the payoff for each player is determined by the matrix of the game. However, in many applications, players choose actions asynchronously, and simultaneity of this process is not guaranteed: it is possible that a player learns the action of another player before making its choice. Delays of choices are controled by the adversary and each player can only secure the worst-case payoff over the adversary's decisions. In this paper we consider such asynchronous versions of arbitrary two-person strategic games and we study how the presence of the asynchronous adversary influences the behavior of the players, assumed to be selfish but rational. We concentrate on deterministic (pure) strategies, and in particular, on the existence and characteristics of pure Nash equilibria in such games. It turns out that the rational behavior of players changes significantly if the decision process is asynchronous. We show that pure Nash equilibria often exist in the asynchronous version of the game even if there were no such equilibria in the synchronous game. We also show that a mere threat of asynchrony in the game may make social optimum a rational choice while it was not rational in the synchronous game.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it