Imitation of honey bees’ concept learning processes using Vector Symbolic Architectures

This article presents a proof-of-concept validation of the use of Vector Symbolic Architectures as central component of an online learning architectures. It is demonstrated that Vector Symbolic Architectures enable the structured combination of features/relations that have been detected by a perceptual circuitry and allow such relations to be applied to novel structures without requiring the massive training needed for classical neural networks that depend on trainable connections.