Special session at IPMU-2022
Title: UncertaintUncertainty, Heterogeneity, Reliability and Explainability in AI
Organisateurs : Salem Benferhat et Karim Tabia
Date et lieu : 12 juillet 2022, Milan.
Description (en anglais) : The last decade has been marked noticeably by the growing use of innovative intelligent systems and applications that rely heavily on AI models and implementations. We are then confronted with new problems and risks, in particular the complexity of the systems and their opacity and the sensitivity of certain critical applications. These are mainly issues of confidence, trust, interpretability and explainability of reasoning and decisions that can be taken automatically.
This special session aims to bring together the AI community addressing issues of reliability, uncertainty, heterogeneity, interpretability, and explainability. In particular, we seek contributions in uncertainty-related knowledge representation and reasoning, reliable and explainable AI, and applications. This will foster cross-fertilization among knowledge representation and reasoning and machine learning.
A Special Issue of a Journal will be scheduled later.
The topics of interest include (but are not limited to):
- Uncertain information representation, reasoning under uncertainty, uncertain data aggregation, and fusion
- Handling heterogeneous data
- Decision making under uncertainty
- Management of imperfect and heterogeneous data
- Reliability and trust, calibration, uncertainty management in machine learning
- Links between knowledge representation, reasoning, decision making, and machine learning
- Explainable and interpretable AI
- Relationships between Knowledge representations/formalisms, Reliability, and Explainability
- Applications of Uncertain, Reliable, and Explainable AI Systems
Programme Le programme est composé de quatorze présentations réparties sur trois sessions. Pour plus détails, cliquer ici (pages 4-7)