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 underlying economic structure and its own preference....

This paper experimentally studies the role of associative memory for belief formation. Realworld information signals are often embedded in memorable contexts. Thus, today’s news, and the contexts they are embedded in, may cue the selective retrieval of similar past news and hence contribute to...

We propose a heuristic switching model of an asset market where the agents' choice of heuristic is consistent with their individual risk aversion. They choose between a fundamentalist and a trend-following rule to form expectations about the price of a risky asset. Given their risk aversion,...

News reports and communication are inherently constrained by space, time, and attention. As a result, news sources often condition the decision of whether to share a piece of information on the similarity between the signal and the prior belief of the audience, which generates a sample selection...

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 experience gained in past rounds to draw inferences from...

This paper analyzes farsighted stable sets when agents have heterogeneous expectations over the dominance paths. We consider expectation functions satisfying two properties of path-persistence and consistency. We show that farsighted stable sets with heterogeneous expectations always exist and...