Titlebook: Rules and Reasoning; 5th International Jo Sotiris Moschoyiannis,Rafael Peñaloza,Dumitru Roma Conference proceedings 2021 Springer Nature Sw

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Deep Learning for the Identification of Decision Modelling Components from Textt modelling the structure and logic of a decision. For decision modellers, analysing textual documents in search for relevant sentences is a time consuming activity. A promising research topic is to build decision models from text. In this paper, an automatic decision modelling component classifier

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Combining Sub-symbolic and Symbolic Methods for Explainabilityhave been developed to provide insights into the GNN decision making process. These are first important steps on the way to explainability, but the generated explanations are often hard to understand for users that are not AI experts. To overcome this problem, we introduce a conceptual approach comb

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Correctness of Automatically Generated Choreography Specificationsrd for specifying business models in structured English, and the . which is a SAT based constraint solver. This paper is concerned with the correctness of such mapping between the generated instance (choreography) in Alloy and the global graph obtained as a direct visual representation of the SBVR model specification.