Papers

8

Total Citations

59

H-Index

4

About

Yoshihiro Tamura’s research lies at the intersection of robotics, cognitive skill analysis, and human-robot interaction, with a particular focus on developing robots that can learn and adapt through value-based systems. His work explores how robots can acquire behaviors by observing humans and other agents, using reinforcement learning and shared value frameworks to bridge the gap between explicit instruction and autonomous learning. Tamura’s most cited paper, “Emulation and behavior understanding through shared values” (2010, 20 citations), introduces a foundational approach for robots to interpret and replicate human actions by aligning internal value systems. He has also made significant contributions to disaster robotics, analyzing firefighting skills for teleoperated robots (2020, 18 citations) and cognitive skill in water discharge activities (2021, 4 citations), addressing critical usability challenges in extreme environments. His research on mutual development of behavior acquisition and recognition (2008, 5 citations) and imitation through observed body clustering (2010, 4 citations) further advances lifelong learning architectures for robots. Tamura’s work is notable for its practical implications in emergency response and its theoretical contributions to value-driven machine learning.

Research Focus

Key Achievements

4
H-Index
8
Papers
59
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Emulation and behavior understanding through shared values
20 citations · 2010
📈 Most Prolific Year: 2008 (3 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: The University of Osaka, National Research Institute of Fire and Disaster

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago