Markov Decision Processes

Abstract

Markov decision processes (MDPs), an established framework for specifying task environments for decision-making agents, are valuable in the behavioral sciences as a formal description of sequential problems faced by animals and people. This article provides a mathematical definition of MDPs, an example application, an introduction to algorithms for finding optimal policies in MDPs, and a list of useful extensions to the basic model.