dynamics considerably differ between gain and loss domains. For gains, learning to be comparably ambiguity averse increases the …

play, imitation, reinforcement learning, and a trial & error process. We test whether subjects try to influence those … number of standard learning algorithms. The learning theories are (unbeknown to subjects) a best response process, fictitious … and that all learning algorithms are subject to exploitation with the notable exception of imitation. The experiment was …

play, imitation, reinforcement learning, and a trial & error process. We test whether subjects try to influence those … number of standard learning algorithms. The learning theories are (unbeknown to subjects) a best response process, fictitious … and that all learning algorithms are subject to exploitation with the notable exception of imitation. The experiment was …

ambiguous lotteries. In the second experiment the sample averages do not converge.If we define fictive learning in an experiment …, then we expect fictive learning in the first experiment, but no fictive learning in the second experiment. The surprising … finding in this paper is the presence of fictive learning in the second experiment. We attribute this counterintuitive result …