Title :
Extracting Refined Rules from Hybrid Neuro-Symbolic Systems
Author :
Villanueva, Jonathan ; Cruz, Vianey ; Reyes, Gerardo ; Benitez, Antonio
Abstract :
In this work is presented the preliminary studies of the development of a system for the extraction of refined rules in artificial neuronal networks from hybrid neuro-symbolic systems. The artificial neuronal networks (ANN) is a distributed massively parallel processor that is prone for the nature to store experimental knowledge and to make it available for the use. However a disadvantage of the ANN is they are considered "black boxes", since they transform the entrances in exits without noticing as this transformation is made.
Keywords :
feature extraction; knowledge representation; neural nets; artificial neuronal networks; hybrid neurosymbolic systems; parallel processor; refined rule extraction; Artificial intelligence; Artificial neural networks; Biological neural networks; Expert systems; Humans; Hybrid intelligent systems; Hybrid power systems; Logic; Neural networks; Student members;
Conference_Titel :
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9490-9
DOI :
10.1109/IJCNN.2006.247260
