Producing Modular Hybrid Rule Bases for Expert Systems

May 2000

Proceedings of the Thirteenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2000)

Volume

Proceedings of the Thirteenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2000)

All Papers

Neurules are a kind of hybrid rules integrating neurocomputing and production rules. Each neurule is represented as an adaline unit. Thus, the corresponding rule base consists of a number of autonomous adaline units (neurules). Due to this fact, a modular and natural rule base is constructed, in contrast to existing connectionist rule bases. In this paper, we present a method for generating neurules from empirical data. We overcome the difficulty of the adaline unit to classify non-separable training examples by introducing the notion of closeness between training examples and splitting each training set into subsets of close examples.