Papers
1
Total Citations
6
H-Index
1
About
Yuki Tamai is a researcher focused at the intersection of human cognition and machine learning, with a particular emphasis on how humans learn continuously and how that process can inform the design of more adaptive robots. Their most notable work, "Analyzing human's continuous learning ability with the reflection cost" (2015), has garnered 6 citations and addresses a critical gap in reinforcement learning frameworks by examining the mental processes of awareness and reflection that precede and shape human learning. This research offers a novel perspective on the "reflection cost"—the cognitive effort required for humans to update their knowledge—providing a foundation for building robots that can learn more naturally from their environments. While their citation count is modest, Tamai’s contributions are significant for their interdisciplinary approach, bridging psychology and robotics to tackle the underexplored pre-learning stages. Their work is particularly valuable for researchers in human-robot interaction and cognitive robotics, offering insights into how machines might emulate the nuanced, continuous learning abilities of humans.
Research Focus
Key Achievements
Top Papers
- 1Analyzing human's continuous learning ability with the reflection cost6 citations · 2015