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Hybrid Connectionist Fuzzy Production System: Towards Building Comprehensive AI

ABSTRACTThe article presents major principles of building complex hybrid systems for knowledge engineering. The systems make use of neural networks (for low level processing), fuzzy systems (for intermediate level processing), and symbolic AI systems (for higher level processing). Knowledge acquisition and rules extraction is considered an important part of the whole system. An experimental environment, Fuzzy COPE, which facilitates building comprehensive AI systems, is described. It consists of data a analysis module, a neural network module, a fuzzy inference module, a production rules module, and a fuzzy rules extraction module. Such an environment makes possible using all of the three paradigms, i.e. fuzzy rules, neural networks and symbolic production rules, as well as other paradigms of soft computing, in one system. A methodology for building comprehensive AI systems is described. The use of Fuzzy COPE for building hybrid systems is illustrated on a test problem for decision making in stock trading...