Architecture of a Cortex Inspired Hierarchical Event Recaller

arXiv:2405.02371v1 Announce Type: cross
Abstract: This paper proposes a new approach to Machine Learning (ML) that focuses on unsupervised continuous context-dependent learning of complex patterns. Although the proposal is partly inspired by some of the current knowledge about the structural and functional properties of the mammalian brain, we do not claim that biological systems work in an analogous way (nor the opposite). Based on some properties of the cerebellar cortex and adjacent structures, a proposal suitable for practical problems is …

abstract architecture arxiv brain claim context continuous cortex cs.ai cs.ar cs.lg cs.ne current event functional hierarchical knowledge machine machine learning paper patterns type unsupervised