, (ii) the resulting efficiency loss, and (iii) the adjustment of the learning rule. …

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

The growing literature on learning in games has produced various results on the predictive success of learning theories … four games in order to check on the robustness of rankings among learning rules across measures. We characterise measures … apply all thus defined measures to 12 learning rules. The results show that rankings are indeed sensitive to the measure …

Rule learning posits that decision makers, rather than choosing over actions, choose over behavioral rules with …. Past works on rule learning have shown that when playing a single game over a number of rounds, players can learn to form … sophisticated beliefs about others. Here we are interested in learning that occurs between games where the set of actions is not …

We investigate learning and the development of the capability to backward induct in children and young adults aged 6 to … differences in learning between age groups and across gender. …

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

This paper aspires to fill a conspicuous gap in the literature regarding learning in games—the absence of empirical … verification of learning rules involving pattern recognition. Weighted fictitious play is extended to detect two-period patterns in … adequately represent the complete learning process of game players. Additionally, standard weighted fictitious play models are …

In this paper, we introduce two new learning models: action-sampling learning and impulse-matching learning. These two … models, together with the models of self-tuning EWA and reinforcement learning, are applied to 12 different 2×2 games and … are two-fold: while the simulations with impulse-matching and action-sampling learning successfully replicate the …