ICAS: An incremental concept acquisition system using attribute-based description

ICAS is an incremental concept acquisition system using attribute-based description. It includes an algorithm for leaming concept, which induces a rule set from an example set based on the probability theory, and an algorithm for refining the rule set. This paper also introduces the learning cycles, a very useful idea of ICAS. In fact, concept acquisition by ICAS is an incremental process consisting of many such learning cycles. Also the design and implementation of ICAS are given.