Title :
Representation of rule-based knowledge in neural networks
Author_Institution :
Dept. of Comput. & Inf. Sci., Florida Univ., Gainesville, FL, USA
fDate :
27 Jun-2 Jul 1994
Abstract :
Shows how to represent rule-based domain knowledge in the framework of a neural network and how to represent neural network knowledge in the format rules for connectionist symbolic processing
Keywords :
inference mechanisms; knowledge representation; neural nets; problem solving; connectionist symbolic processing; neural network knowledge; rule-based knowledge; Backpropagation; Buildings; Computational Intelligence Society; Councils; Intelligent networks; Intelligent structures; Intelligent systems; Network topology; Neural networks; Problem-solving;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374506
