Knowledge Consolidation and Inference in the Integrated Neuro-Cognitive Architecture

Recent advances in cognitive neuroscience, psychology, and AI provide remarkable insights toward building an integrated framework for human-level, general intelligence. This article presents Integrated Neuro-Cognitive Architecture (INCA), which emulates the putative functional aspects of various major brain systems via a learning memory modeling approach. INCA features scalable structural and parameter self-organizing mechanisms to form high-level symbolic knowledge from low-level data and knowledge exploitation mechanisms based on plausible consolidation and inference cycles, respectively.