Multi-layer Cortical Learning Algorithms

Abstract

Hierarchical Temporal Memory (HTM) is a model with hierarchically connected modules doing spatial and temporal pattern recognition, as described by Jeff Hawkins in his book entitled On Intelligence. Cortical Learning Algorithms (CLAs) comprise the second implementation of HTM. CLAs are an attempt by Numenta Inc. to create a computational model of perceptual analysis and learning inspired by the neocortex in the brain. In its current state only an implementation of one isolated region has been completed. The goal of this paper is to test if adding a second higher level region implementing CLAs to a system with just one region of CLAs, helps in improving the prediction accuracy of the system. The LIDA model (Learning Intelligent Distribution Agent - LIDA is a cognitive architecture) can use such a hierarchical implementation of CLAs for its Perceptual Associative Memory.