AI and memory: Studies towards equipping a robot with a sparse distributed memory

Abstract

Traditional approaches to Artificial Intelligence (AI) and Robotics seem only to provide advances at a very slow pace. Many researchers agree that new, different approaches are needed to provide a breakthrough and allow the construction of robots with human-like capacities. Our approach consists in navigating a robot using vision a Sparse Distributed Memory (SDM), a kind of associative memory based on the properties of high dimensional binary spaces, which, in theory, exhibits some human-like behaviours. During learning the robot will store sequences of images in the SDM. During execution the robot will follow the sequence of images that is closest to its current view. Preliminary results show that the memory can store and predict sequences of images with a small error tolerance.