Affiliations: Dipartimento di Informatica – Scienza e Ingegneria (DISI), Alma Mater Studiorum–Università di Bologna, Italy
Corresponding author: Roberta Calegari, Dipartimento di Informatica – Scienza e Ingegneria (DISI), Alma Mater Studiorum–Università di Bologna, Italy. E-mail: [email protected].
Abstract: The more intelligent systems based on sub-symbolic techniques pervade our everyday lives, the less human can understand them. This is why symbolic approaches are getting more and more attention in the general effort to make AI interpretable, explainable, and trustable. Understanding the current state of the art of AI techniques integrating symbolic and sub-symbolic approaches is then of paramount importance, nowadays—in particular in the XAI perspective. This is why this paper provides an overview of the main symbolic/sub-symbolic integration techniques, focussing in particular on those targeting explainable AI systems.
Keywords: XAI, symbolic and sub-symbolic AI, explainability, interpretability, trustable