We present an experiment for the study of learning in a complex task which requires both memorisation and the ability …

reinforcement learning wherein individuals become unduly optimistic after receiving good returns. In sharp contrast, there is little …

thesis makes two distinct contributions in the field of learning game theory and one in the field of evolutionary game theory … tractability, and also to illustrate, complement and extend various analytical derivations. The two extensions to learning game … one of two alternative decision-making processes –case-based reasoning or reinforcement learning– that have received …

different cognitive abilities learn differently, we estimate a structural model of learning based on level-k reasoning. We find …

Bateson. Learning requires to recognize a series of situations as identical and then to observe the effect of given variables … hypothesis to be continuously tested. This vision of bounds and learning has many implications for the debate on rationality and …

Dynamic models of learning and adaptation have provided realistic predictions in terms of voting behavior. This study … choice. We test through panel data methods an outcome-based learning mechanism based on the following assumptions: (a) people … affiliation reinforce this adaptive behavior. The analysis also investigates the intensity of the learning feedback …

Dynamic models of learning and adaptation have provided realistic predictions in terms of voting behavior. This study … aims at contributing to their scant empirical verification. We develop a learning algorithm based on bounded rationality … estimating the pattern of learning process through a two-stage econometric model. The analysis links voting behavior to past …