Whole brain Probabilistic Generative Model toward Realizing Cognitive Architecture for Developmental Robots

Taniguchi, Tadahiro, Yamakawa, Hiroshi, Nagai, Takayuki, Doya, Kenji, Sakagami, Masamichi, Suzuki, Masahiro, Nakamura, Tomoaki, Taniguchi, Akira

arXiv.org Artificial Intelligence 

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.

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