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 …

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 …

learning processes exhibited by players. …

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 …

unknown value. A winner’s curse phenomenon arises when subjects bid too high and make losses. Learning direction theory can … quantitative predictions on the basis of learning direction theory. We also look at monotonic ladder processes. It is shown that …