The goal of LEADER is to investigate how experiential learning occurs in dynamic environments. Thus, in LEADER, learning is defined as the processes according to which past experience affects current choice behavior. Review of the economics and psychology literature shows that we have a fairly rich knowledge about the factors that drive human learning in repeated decision tasks (static decision environments). However, we know little about how learning occurs in dynamic environments, where the values of the environmental variables relevant to the decision making process are affected by shocks over time. In LEADER, I collect data from laboratory experiments on purely feedback-driven decisions in dynamic environments, and use these data to develop and test new computational models of learning that endogenize the processes of shock detection and adaptation. The feasibility of LEADER is guaranteed by the academic strength of the PI, the hired postdoctoral student, and hosting institution.
|Effective start/end date||01/09/2017 → 31/08/2021|