LearnSDM: Model Learning for Sequential Decision Making
Smart systems need to plan ahead, for instance to decide when to charge your
electric vehicle, when to heat your home or how to guide you to your
destination. Algorithms for sequential decision making allow for smart
decisions given an uncertain future, but require models of the system as
input. This project combines machine learning and model checking to
learn and evaluate such models based on historical data.