An Artificial Intelligence framework for the resolution of Systems Engineering problems


At present time, the experienced AI practitioners can find many different frameworks and libraries to produce Artificial Intelligence solutions (TensorFlow, CNTK, Weka, Keras, Theano, etc.). Most of these environments allow the development of machine learning, AI, NLP and other algorithms configuring and filtering information and data. When applied to Systems Engineering problems, the needed data is usually hidden in different very specific tools like RMS, MBSE tools, 3D models, etc. The presentation shows a new approach that brings Systems Engineering data to the AI frameworks by taking advantage of the modern Interoperability standards for information sharing. A special emphasis will be made to OSLC and System Representation Language (SRL) approaches to provide access to SE information for AI purposes.


Juan Llorens – UC3M & The REUSE Company