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Neuro-symbolic Computation for XAI: Towards a Unified Model

Giuseppe Pisano, Giovanni Ciatto, Roberta Calegari, Andrea Omicini
The idea of integrating symbolic and sub-symbolic approaches to make intelligent systems (IS) understandable and explainable is at the core of new fields such as neuro-symbolic computing (NSC). This work lays under the umbrella of NSC, and aims at a twofold objective. First, we present a set of guidelines aimed at building explainable IS, which leverage on logic induction and constraints to integrate symbolic and sub-symbolic approaches. Then, we reify the proposed guidelines into a case study to show their effectiveness and potential, presenting a prototype built on the top of some NSC technologies.
Keywords: XAI, Hybrid Systems, Neural Networks, Logical Constraining
09 2020.