What is ART?

Adaptive Resonance Theory (ART) is a neural network architecture developed by Gail Carpenter and Stephen Grossberg. It is capable of learning in a stable fashion without forgetting previously learned patterns, addressing the 'stability-plasticity dilemma'. ART networks are unsupervised learning models, often used for clustering and pattern recognition tasks. They are particularly noted for their ability to handle new, unseen data without disrupting existing knowledge.