  Building a humanlike integrative artificial cognitive system, that is, an
artificial general intelligence, is one of the goals in artificial intelligence
and developmental robotics. Furthermore, a computational model that enables an
artificial cognitive system to achieve cognitive development will be an
excellent reference for brain and cognitive science. This paper describes the
development of a cognitive architecture using probabilistic generative models
(PGMs) to fully mirror the human cognitive system. The integrative model is
called a whole-brain PGM (WB-PGM). It is both brain-inspired and PGMbased. In
this paper, the process of building the WB-PGM and learning from the human
brain to build cognitive architectures is described.
