作者：Basu, Pathikrit; Echenique, Federico
作者单位：California Institute of Technology
摘要：We study the degree of falsifiability of theories of choice. A theory is easy to falsify if relatively small data sets are enough to guarantee that the theory can be falsified: the Vapnik-Chervonenkis (VC) dimension of a theory is the largest sample size for which the theory is never falsifiable. VC dimension is motivated strategically. We consider a model with a strategic proponent of a theory and a skeptical consumer, or user, of theories. The former presents experimental evidence in favor o...
作者：Bervoets, Sebastian; Bravo, Mario; Faure, Mathieu
作者单位：Aix-Marseille Universite; Centre National de la Recherche Scientifique (CNRS); Aix-Marseille Universite; Universidad de Santiago de Chile
摘要：While payoff-based learning models are almost exclusively devised for finite action games, where players can test every action, it is harder to design such learning processes for continuous games. We construct a stochastic learning rule, designed for games with continuous action sets, which requires no sophistication from the players and is simple to implement: players update their actions according to variations in own payoff between current and previous action. We then analyze its behavior i...
