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

• URL: http://arxiv.org/abs/2103.08183v1
• Date: Mon, 15 Mar 2021 07:42:04 GMT
• Title: Whole brain Probabilistic Generative Model toward Realizing Cognitive Architecture for Developmental Robots
• Authors: Tadahiro Taniguchi, Hiroshi Yamakawa, Takayuki Nagai, Kenji Doya, Masamichi Sakagami, Masahiro Suzuki, Tomoaki Nakamura, Akira Taniguchi
• Abstract summary: Building a humanlike integrative artificial cognitive system, that is, an artificial general intelligence, is one of the goals in artificial intelligence and developmental robotics. This paper describes the development of a cognitive architecture using probabilistic generative models (PGMs) to fully mirror the human cognitive system.
• Score: 8.941833998120904
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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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