This essay links some of my own work on expectations, learning and bounded rationality to the inspiring ideas of Jean …-Michel Grandmont. In particular, my work on consistent expectations and behavioral learning equilibria may be seen as formalizations of … JMG's ideas of self-fulfilling mistakes. Some of our learning-to-forecast laboratory experiments with human subjects have …

dynamics considerably differ between gain and loss domains. For gains, learning to be comparably ambiguity averse increases the …

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 …

The paper investigates social-learning when the information structure is not commonly known. Individuals repeatedly … interact in social-learning settings with distinct information structures. In each round of interaction, they use their … behavior in the long-run if and only if individuals distinguish social-learning settings and receive rich feedback after each …

Adaptive learning introduces persistence in the evolution of agents' beliefs over time. For applied purposes this is a … convenient feature to help explain why economies present sluggish adjustments towards equilibrium. The pace of learning is … document renewed empirical calibrations of plausible gain values for adaptive learning applications to macroeconomic data. We …

This exercise offers an innovative learning mechanism to model economic agent's decision-making process using a deep … reinforcement learning algorithm. In particular, this AI agent is born in an economic environment with no information on the … adjusting its actions accordingly (i.e., online learning). I illustrate that the economic agent under deep reinforcement …