title: A knowledge-base generating hierarchical fuzzy-neural controller.
abstract: We present an innovative fuzzy-neural architecture that is able to automatically generate a knowledge base, in an extractable form, for use in hierarchical knowledge-based controllers. The knowledge base is in the form of a linguistic rule base appropriate for a fuzzy inference system. First, we modify Berenji and Khedkar's (1992) GARIC architecture to enable it to automatically generate a knowledge base; a pseudosupervised learning scheme using reinforcement learning and error backpropagation is employed. Next, we further extend this architecture to a hierarchical controller that is able to generate its own knowledge base. Example applications are provided to underscore its viability.
authors.affiliation: Rensselaer Polytech. Inst., Troy, NY.
authors.forename: R M
authors.initials: RM
authors.lastname: Kandadai
authors.forename: J M
authors.initials: JM
authors.lastname: Tien