This research focusses on AI techniques to assist humans in making important and complex decisions. Based on data sets with historical decisions made based on certain events and the consequences, AI will be applied to identify the best options in terms of multiple objectives. The goal is to combine data-driven approaches with human expert knowledge into a hybrid solution that outperforms both.

The research targets 2 specific application domains: recommender systems and scheduling. Recommender systems assist users in decision making processes, such as content selection, thereby tackling the problem of information overload. Application domains are personalised suggestions for movies, music, meals, or physical activities.

Scheduling algorithms plan jobs or activities at specific times, thereby assigning the required resources and taking into account the necessary constraints. Application domains are the planning of production in manufacturing industry, maintenances, or staff scheduling.