Structural Estimation of Markov Decision Processes in High-Dimensional State Space with Finite-Time Guarantees

arXiv:2210.01282v3 Announce Type: replace
Abstract: We consider the task of estimating a structural model of dynamic decisions by a human agent based upon the observable history of implemented actions and visited states. This problem has an inherent nested structure: in the inner problem, an optimal policy for a given reward function is identified while in the outer problem, a measure of fit is maximized. Several approaches have been proposed to alleviate the computational burden of this nested-loop structure, but these …

abstract agent arxiv cs.ai cs.lg decision decisions dynamic econ.em history human markov observable policy processes space state stat.ml type