Real-World Robot Control Based on Contrastive Deep Active Inference With Demonstrations

Real-World Robot Control Based on Contrastive Deep Active Inference With Demonstrations

Despite significant advances in robotics and deep learning, the ability of robots to perceive and act remain far below that of humans. To bridge this gap, we utilize active inference, a framework based on the free-energy principle that accounts for various human brain functions. Despite the utility...

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Bibliographic Details
Main Authors: Kentaro Fujii, Takuya Isomura, Shingo Murata
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Active inference
robot learning
learning from demonstration
world model
free energy principle
contrastive learning
Online Access:https://ieeexplore.ieee.org/document/10710342/
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https://ieeexplore.ieee.org/document/10710342/

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