In the last decade, we have seen an exponential increase in the number of devices connected to the Internet, with a commensurate explosion in the availability of data. New applications such as those related to smart cities exemplify the need for principled techniques for automated intelligent decision making based on available data. Many decision-making problems require reasoning in large and complex state spaces, sometimes under stringent time constraints. The nature of these problems suggests that planning approaches could be used to fifind solutions e!ciently. Automated planning is the basis for addressing a diversity of problems beyond classical planning such as automated diagnosis, controller synthesis, and story understanding. Nevertheless, many planning paradigms make assumptions that do not hold in real-world settings