Perception processing for general intelligence: Bridging the symbolic/subsymbolic gap

Abstract

Bridging the gap between symbolic and subsymbolic representations is a - perhaps the - key obstacle along the path from the present state of AI achievement to human-level artificial general intelligence. One approach to bridging this gap is hybridization - for instance, incorporation of a subsymbolic system and a symbolic system into a integrative cognitive architecture. Here we present a detailed design for an implementation of this approach, via integrating a version of the DeSTIN deep learning system into OpenCog, an integrative cognitive architecture including rich symbolic capabilities. This is a "tight" integration, in which the symbolic and subsymbolic aspects exert detailed real-time influence on each others' operations. An earlier technical report has described in detail the revisions to DeSTIN needed to support this integration, which are mainly along the lines of making it more "representationally transparent," so that its internal states are easier for OpenCog to understand. © 2012 Springer-Verlag.