Abstract
This work suggests a novel approach to autonomous systems development linking autonomous technology to an integrated cognitive architecture with the aim of supporting a common artificial general intelligence (AGI) development. The paper provides a summary of strengths and weaknesses of some of the most known cognitive architecture and highlights how to support a generic artificial intelligent approach rather than ad hoc solutions. It also proposes objective evaluation criteria to assess a cognitive architecture. Finally, the proposed cognitive architecture is introduced: a Deep-Learning Artificial Neural Cognitive Architecture (D-LANCA), which aims to overcome current limits of cognitive frameworks for autonomous systems with the view to create a common artificial general intelligent (AGI) cognitive approach across industries.
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