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 …

In this paper, we introduce two new learning models: impulse-matching learning and action-sampling learning. These two … models together with the models of self-tuning EWA and reinforcement learning are applied to 12 different 2 x 2 games and … their results are compared with the results from experimental data. We test whether the models are capable of replicating …

reinforcement learning models than with belief-based models. Showing level-2 rationality (i.e., reasoning about others' beliefs) is … process level to the validity of modeling behavior using low-rationality reinforcement learning models …

In this paper, we introduce two new learning models: impulse-matching learning and action-sampling learning. These two … models together with the models of self-tuning EWA and reinforcement learning are applied to 12 different 2 x 2 games and … their results are compared with the results from experimental data. We test whether the models are capable of replicating …

reinforcement learning models than with belief-based models. Showing level-2 rationality (i.e., reasoning about others' beliefs) is … process level to the validity of modeling behavior using low-rationality reinforcement learning models. -- coordination … ; minority game ; market efficiency ; information ; self-organization ; reinforcement learning …

In this paper we introduce four new learning models: impulse balance learning, impulse matching learning, action …-sampling learning, and payof-sampling learning. With this models and together with the models of self-tuning EWA learning and … reinforcement learning, we conduct simulations over 12 different 2 x 2 games and compare the results with experimental data obtained …

reinforcement learning models than with belief-based models. Showing level-2 rationality (i.e., reasoning about others' beliefs) is … process level to the validity of modeling behavior using low-rationality reinforcement learning models. …

opportunities to identify learning rules, since on networks (compared to, e.g., random matching) more rules differ in terms of their … information they consult before making their choices. We use these data to estimate learning types using finite mixture models … find that learning depends on network position. Participants in more complex environments (with more network neighbors …