Optimal Decision Making & Reinforcement Learning



The last few decades have seen an enormous increase in the amounts of data being generated; very often, this data is available not only in a static sense but also in a dynamic context. At the same time, the availability of computational power has grown dramatically. The combination of abundant data sets and computational resources creates huge opportunities for better decision making via (mathematical) optimization techniques and learning algorithms. We use the word “analytics” to capture this process: assessing the data, leveraging them for predictions, specifying a problem, and using mathematical techniques to solve the problem, in order to ultimately improve decisions. Data, models, and techniques are jointly needed to achieve maximum impact. This course extends the knowledge of students from descriptive and predictive analytics to prescriptive analytics and introduces the students to the fundamental tools to use this data for learning optimal decision strategies.
Cursusperiode1/09/22 → …