payoff-based learning models are simulated in order to understand individual learning behavior in distributed systems. Under … the serial mechanism the payoff-assessment learning model (Sarin and Vahid (1997)) provides the best fit to the data …, followed by the experience-weighted attraction learning model (Camerer and Ho (1999)), which in turn, is followed by a simple …

decision behavior (like learning and expectation formation), reasoning, and the connection between bounded rationality and …

learning procedures. We consider the Stochastic Gradient-Algorithm as a boundedly rational learning procedure in an univariate … influence of the forecast feedback is limited the learning agents cannot destabilize the model and learn to form rational …

Adaptive learning and punishment are highly prominent competing explanations for ultimatum game behavior. We report on … an experiment that considers each theory in stand-alone form, so that one does not rely on the other in any substantial … way. Our data exhibits patterns for which punishment can account but learning by itself cannot. Initial play varies …

equilibrium of the game does not organize the individual data, two individual learning models are studied: one following a … predictive value of such learning models is found to be poor. …

Recently there has been much theoretical and experimental work on learning in games. However, learning usually means … "learning about the strategic behavior of opponents" rather than "learning about the game" as such. In contrast, here we report … on an experiment designed to test whether players learn a) the relevant features of the payoff structure of a 2x2 game (e …

and that all learning algorithms are subject to exploitation with the notable exception of imitation. The experiment was …We use an experiment to explore how subjects learn to play against computers which are programmed to follow one of a … number of standard learning algorithms. The learning theories are (unbeknown to subjects) a best response process, fictitious …