35 citations · 103 across the 7 of their papers we have counts for
5 papers · 1 filter
The whole brain architecture approach: Accelerating the development of artificial general intelligence by referring to the brain
Hiroshi Yamakawa
The vastness of the design space created by the combination of a large number of computational mechanisms, including machine learning, is an obstacle to creating an artificial gene…
A Whole Brain Probabilistic Generative Model: Toward Realizing Cognitive Architectures for Developmental Robots
Tadahiro Taniguchi, Hiroshi Yamakawa, Takayuki Nagai +5
Building a humanlike integrative artificial cognitive system, that is, an artificial general intelligence (AGI), is the holy grail of the artificial intelligence (AI) field. Furthe…
Hippocampal formation-inspired probabilistic generative model
Akira Taniguchi, Ayako Fukawa, Hiroshi Yamakawa
In building artificial intelligence (AI) agents, referring to how brains function in real environments can accelerate development by reducing the design space. In this study, we pr…
Autonomous Self-Explanation of Behavior for Interactive Reinforcement Learning Agents
Yosuke Fukuchi, Masahiko Osawa, Hiroshi Yamakawa +1
In cooperation, the workers must know how co-workers behave. However, an agent's policy, which is embedded in a statistical machine learning model, is hard to understand, and requi…
Bayesian Inference of Self-intention Attributed by Observer
Yosuke Fukuchi, Masahiko Osawa, Hiroshi Yamakawa +2
Most of agents that learn policy for tasks with reinforcement learning (RL) lack the ability to communicate with people, which makes human-agent collaboration challenging. We belie…