An adaptive associative memory system based on autonomous reaction between image memories

Abstract

To construct a “thinking-like” processing system, a new architecture of an adaptive associative memory system is proposed. This memory system treats “images” as basic units of information, and adapts to the environment of the external world by means of autonomous reactions between the images. The images do not have to be clear, distinct symbols or patterns; they can be ambiguous, indistinct symbols or patterns as well. This memory system is a kind of neural network made up of nodes and links called a localist spreading activation network. Each node holds one image in a localist manner. Images in high-activity nodes interact autonomously and generate new images and links. By this reaction between images, various forms of images are generated automatically under constraints of links with adjacent nodes. In this system, three simple image reaction operations are defined. Each operation generates a new image by combining pseudofigures or features and links of two images.