Adaptive resonance theory is a quantitative explanation of learning and memory developed by Gail Carpenter, Stephen Grossberg and others. ART1 and ART2 are neural net architectures based on adaptive resonance theory. each of thess neural nets self-organizes the input data into categories with the variation allowed within a category depending on a user selected vigilance parameter . ART1 is used for binary input, ART2 for continuous input [Carpenter & Grossberg, 1987a, 1987b].