An architecture for autonomous agents integrating symbolic and behavioral processing

Abstract

A new architecture for autonomous agents is proposed. The architecture integrates the symbolic and the behavioral processing of data coming from the robot sensors. The integration is based on the introduction of a conceptual space representation that links the subconceptual level, which is a repository of behavioral modules, with the symbolic level, in which rich symbolic descriptions of the agent environment take place.