TRR 318 - Project C02: Interactive learning of explainable, situation-adapted decision models
Overview
The focus of Project C02 investigates a novel
approach through which the space of possible models explaining a certain
decision can be explored interactively by a user until a model is found that
satisfies the needs of the user in terms of the trade-off between accuracy and
model complexity. The project defines and explores a refinement relation that
defines a lattice as an explanation space from which explanations can be
selected.
Key Facts
- Project type:
- Forschung
- Project duration:
- 07/2021 - 12/2025
More Information
Publications
Generation of Explanatory Content and Requirements for Social XAI
K. Främling, K. Thommes, B. Wrede, in: Social Explainable AI, Springer Nature Singapore, Singapore, 2026.
Measuring the Outcome of sXAI
K. Thommes, in: Social Explainable AI, Springer Nature Singapore, Singapore, 2026.
Operationalizing Social Interaction
H. Wachsmuth, K. Thommes, M. Alshomary, in: Social Explainable AI, Springer Nature Singapore, Singapore, 2026.
Exploration of Explaining Content
K. Främling, B. Wrede, K. Thommes, in: Social Explainable AI, Springer Nature Singapore, Singapore, 2026.
Interaction History in Social XAI
Show all publications
K. Thommes, K. Främling, B. Wrede, S. Kubler, in: Social Explainable AI, Springer Nature Singapore, Singapore, 2026.