A Whole Brain Probabilistic Generative Model

Approach for Cognitive Architecture of Developmental Robots

Abstract

This paper describes a concept for building a human-like integrative artificial cognitive system, that is, an artificial general intelligence (AGI). The aim is to develop a computational model that enables an artificial system to achieve cognitive development by referring human brain structure. The approach is called a whole brain probabilistic generative model (WB-PGM). WB-PGM is based on two ideas: (1) brain-inspired AI, learning human brain architecture to build human-level intelligence, and (2) a probabilistic generative model(PGM)-based cognitive architecture to develop a cognitive system for developmental robots by integrating PGMs.