Neural network learning and expert systems
Neural network learning and expert systems
Hybrid Neural Network and Expert Systems
Hybrid Neural Network and Expert Systems
Neural Networks in Computer Intelligence
Neural Networks in Computer Intelligence
A Recency Inference Engine for Connectionist Knowledge Bases
Applied Intelligence
An Efficient Hybrid Rule Based Inference Engine with Explanation Capability
Proceedings of the Fourteenth International Florida Artificial Intelligence Research Society Conference
Neuro-Symbolic Approaches for Knowledge Representation in Expert Systems
International Journal of Hybrid Intelligent Systems
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Neurules are a type of hybrid rules combining a symbolic and a connectionist representation. There are two disadvantages of neurules. The first is that the created neurule bases usually contain multiple representations of the same piece of knowledge. Also, the inference mechanism is rather connectionism oriented than symbolism oriented, thus reducing naturalness. To remedy these deficiencies, we introduce an extension to neurules, called multi-neurules, and an alternative inference process, which is rather symbolism oriented. Experimental results comparing the two inference processes are also presented.