TRR 318-2 - Project C02: Interactive learning of explainable, situation-adapted decision models

C02 aims to optimize ML-based decision support systems and human-AI interaction in order to improve decision-making. We focus on explainable and transparent models that take the decision context into account. We are focusing on prescriptive decision-making with partial feedback, where we not only consider the long-term impact of decisions but also improve the integration of Decision Makers (DMs) by accounting for their mental models and involving them in cases for exploration.