Papers

3

Total Citations

37

H-Index

3

About

Yoko Yamaguchi is a pioneering researcher in distributed autonomous robotics and neural dynamics, with a focus on understanding communication and adaptive behavior in complex systems. Her seminal 1994 paper on the "Mutual-Entrainment-Based Communication Field" introduced a groundbreaking framework for autonomous coordinative control in unpredictable environments, laying the foundation for decentralized robotic coordination. This work, which has garnered 17 citations, remains influential in robotics and self-organizing systems. Yamaguchi further advanced the field by exploring neural dynamics through her 2014 study on communication in complex hetero systems (10 citations), bridging robotics with biological principles. Her 2008 research on "Context-Dependent Adaptive Behavior Generated in the Theta Phase Coding Network" (10 citations) demonstrated how neural oscillatory patterns can produce flexible, context-sensitive responses, offering insights into both artificial intelligence and cognitive neuroscience. Yamaguchi’s interdisciplinary approach, merging robotics, neural computation, and complex systems theory, has established her as a key figure in understanding how distributed agents achieve coordinated, adaptive behavior. Her work continues to inspire researchers in autonomous systems and neural modeling.

Research Focus

Key Achievements

3
H-Index
3
Papers
37
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
Mutual-Entrainment-Based Communication Field in Distributed Autonomous Robotic System — Autonomous coordinative control in unpredictable environment —
17 citations · 1994
📈 Most Prolific Year: 1994 (1 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Tokyo Denki University, RIKEN, RIKEN Center for Emergent Matter Science

Top Papers

  1. 1
  2. 2
  3. 3

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago