Notice bibliographique
Résumé
This essay, an offshoot of research for Volume II of A History of Game Theory, will examine the encounters of game theory and experimentation in the two decades following the Second World War, and the adoption of experimental games as a characteristic feature of game theory in contrast to the much more limited use of experimentation by economists uninfluenced by game theory. The theory of games of strategy has followed a distinctive path in attempting to confront its abstract theory of conflict and cooperation with evidence about economic and social behavior. In the first twenty years after von Neumann and Morgenstern’s Theory of Games and Economic Behavior (1944), game theorists began, at first tentatively and then on a large scale, to conduct strategic games as controlled experiments. In contrast, another new sub-discipline, macroeconomics, devoted its efforts to regression analysis of large, simultaneous equations models during the same years: Cowles monographs edited or co-edited by Tjalling Koopmans developed econometric theory for the estimation and identification of simultaneous equations models, while Lawrence Klein and his associates constructed models growing beyond the Brookings and Wharton models to CANDIDE (the Canadian Interdepartmental Econometric Model) with more than two thousand equations and finally Project LINK, which connects such models of 79 countries or groups of countries. Demand studies in microeconomics also focussed on econometrics applied to non-experimental data. Just as survey data has been so little used in economics that the advocacy by Blinder (1990) of “Learning by Asking Those Who Are Doing” struck its audience as quite daring, experiments played little role in economics apart from game theory. This was in sharp contrast to psychology: it is noteworthy that just as the use of survey data in economics was sustained in the 1950s by George Katona, who was cross-appointed in psychology and economics at the University of Michigan, the psychologist Sidney Siegel played a crucial role in promoting experimental games in economics. Some attempts had been made by psychologists (notably L.L.Thurstone 1931; cf. Mosteller and Nogee 1951) to measure preferences experimentally, but, in an influential paper, W. Allen Wallis and Milton Friedman (1942) denied that such experiments had any value for economics. Thirty experiments in strategic interaction were published by the time of the first survey of experimental gaming by Anatol Rapoport and Carol Orwant (1962). The subsequent growth of the literature was signaled by the introduction of an experimental gaming section edited by Rapoport in the Journal of Conflict Resolution in 1965, and Andrew Colman (1982, 12) reports estimates of over a thousand experimental gaming studies published by 1972, and some 1500 by the early 1980s. Kagel and Roth’s Handbook of Experimental Economics needed more than 700 pages to survey its subject in 1995 (including experiments in economics not limited to studies of strategic interaction). A specialized journal, Experimental Economics, began publication in June 1998; a majority of the articles in its inaugural issue were game-theoretic. A four-paper Economic Journal symposium on experimental economics (Loomes 1999) was the subject of an article in The Economist (May 8,1999).
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,172 | 0,032 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».