Aspects of integration of explicit and implicit knowledge in connectionist expert systems

A unified approach for integrating explicit and implicit knowledge in connectionist expert systems is proposed. The explicit knowledge is represented by discrete fuzzy rules, which are directly mapped into an equivalent multi-purpose neural network based on the MAPI neuron (A.F. Rocha et al., 1992). The learning result is a refinement process of data sets, which is represented in a module (or combination of modules) of classical feedforward structures incorporating implicit fuzzy rules. The combination of explicit and implicit knowledge modules is viewed as an iterative process in knowledge acquisition and refinement.