A well known problem in economics is to describe properly a situation where N agents are repeatedly competing to use the same limited resource. A version of this problem is known in the literature as the El Farol game: week after week N agents face the decision whether to go or not to go to a...

The rational expectations hypothesis is supported if rational expectations are stable with respect to reasonable learning procedures. We consider the Stochastic Gradient-Algorithm as a boundedly rational learning procedure in an univariate ARX-Model with forecast feedback. We prove that whenever...

We develop a learning rule that generalises the well known fading memory learning in the sense that the weights attached to the available time series data are not constant and are updated in light of the prediction error(s). The underlying idea is that confidence in the available data will be...

This paper explores the question whether boundedly rational agents learn to behave optimally when asked to voluntarily contribute to a public good. The decision process of individuals is described by an Evolutionary Algorithm. We find that the contribution level converges towards the Nash...

In our model, individual consumers follow simple behavioral decision rules based on imitation and habit as suggested in consumer research, social learning, and related fields. Demand can be viewed as the outcome of a population game whose revision protocol is determined by the consumers'...

We analyze the strategic behavior of firms when demand is determined by a rule of thumb behavior of consumers. We assume consumer dynamics where individual consumers follow simple behavioral decision rules governed by imitation and habit as suggested in consumer research. On this basis, we...

We consider the situation in which individuals in a finite population must repeatedly choose an action yielding an uncertain payoff. Between choices, each individual may observe the performance of one other individual. We search for rules of behavior with limited memory that increase expected...

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 play, imitation, reinforcement learning, and a trial...

In this note we study a very simple trial & error learning process in the context of a Cournot oligopoly. Without any knowledge of the payoff functions players increase, respectively decrease, their quantity by one unit as long as this leads to higher profits. We show that despite the absence of...

We present a formal model of symmetric n-firm Cournot oligopoly with a heterogeneous population of profit optimizers and imitators. Imitators mimic the output decision of the most successful firms of the previous round a la Vega-Redondo (1997). Optimizers play myopic best response to the...