{"title":"对称的量子响应平衡:表示与应用","authors":"Evan Friedman, Felix Mauersberger","doi":"10.1145/3490486.3538351","DOIUrl":null,"url":null,"abstract":"Quantal Response Equilibrium (QRE) generalizes Nash equilibrium (NE) by allowing players to make probabilistic mistakes in best responding to others' behavior while maintaining fixed-point consistency. QRE has had considerable success in explaining empirically observed deviations from NE ([3]) and so has become a standard benchmark for analyzing experimental data. QRE is nothing more than equilibrium with noisy players, and the only modelling consideration is how to model this noise: one must select the admissable family of noise structures. The literature has proposed a number of such families, ranging from the very precise to the very flexible. At one extreme, noise is governed by a specific parametric family, whereas on the other, there are so many degrees of freedom that the model is difficult to reject.","PeriodicalId":209859,"journal":{"name":"Proceedings of the 23rd ACM Conference on Economics and Computation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Quantal Response Equilibrium with Symmetry: Representation and Applications\",\"authors\":\"Evan Friedman, Felix Mauersberger\",\"doi\":\"10.1145/3490486.3538351\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Quantal Response Equilibrium (QRE) generalizes Nash equilibrium (NE) by allowing players to make probabilistic mistakes in best responding to others' behavior while maintaining fixed-point consistency. QRE has had considerable success in explaining empirically observed deviations from NE ([3]) and so has become a standard benchmark for analyzing experimental data. QRE is nothing more than equilibrium with noisy players, and the only modelling consideration is how to model this noise: one must select the admissable family of noise structures. The literature has proposed a number of such families, ranging from the very precise to the very flexible. At one extreme, noise is governed by a specific parametric family, whereas on the other, there are so many degrees of freedom that the model is difficult to reject.\",\"PeriodicalId\":209859,\"journal\":{\"name\":\"Proceedings of the 23rd ACM Conference on Economics and Computation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 23rd ACM Conference on Economics and Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3490486.3538351\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 23rd ACM Conference on Economics and Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3490486.3538351","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Quantal Response Equilibrium with Symmetry: Representation and Applications
Quantal Response Equilibrium (QRE) generalizes Nash equilibrium (NE) by allowing players to make probabilistic mistakes in best responding to others' behavior while maintaining fixed-point consistency. QRE has had considerable success in explaining empirically observed deviations from NE ([3]) and so has become a standard benchmark for analyzing experimental data. QRE is nothing more than equilibrium with noisy players, and the only modelling consideration is how to model this noise: one must select the admissable family of noise structures. The literature has proposed a number of such families, ranging from the very precise to the very flexible. At one extreme, noise is governed by a specific parametric family, whereas on the other, there are so many degrees of freedom that the model is difficult to reject.