Hiroshi Sato
1 indexed paper
Recent (6 mo)
1With code
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0Benchmarked
0Publications per year
126
Top categories
Robotics×1AI×1
Frequent co-authors
Research Timeline
2026
Visualizing Latent Phase Structures in Locomotion Policies: A Multi-Environment Study with Temporal Feature Extension
The paper proposes a novel framework to visualize and uncover latent, structured motion phases in deep reinforcement learning locomotion policies by augmenting state observations with action and next-state information.
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