Alan Perotti Guido Boella Artur d'Avila Garcez

Learning and extracting tacit knowledge from processes using the Neural- Symbolic paradigm

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The traditional dualism between tacit and explicit knowledge is renewed, concerning the field of Artificial Intelligence, in the contraposition between logics and subsymbolic models (for instance, the connectionist paradigm). In this article we propose a hybrid system that integrates a logical representation of explicit knowledge with a mechanism for inference and learning about tacit knowledge through neural networks. In particular, we describe the application of this system in the context of business process management.


  • Tacit Knowledge
  • Explicit Knowledge
  • Neural Networks
  • Temporal Logic
  • Business Process Management


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