Fumiko Kiriake
Papers
2
Total Citations
7
H-Index
2
About
Fumiko Kiriake’s research lies at the intersection of autonomous robotics, reinforcement learning, and cognitive-inspired artificial intelligence. Her most cited work, “Brain-Inspired Emergence of Behaviors in Mobile Robots by Reinforcement Learning with Internal Rewards” (2008, 4 citations), introduces a groundbreaking framework that equips mobile robots with internal motivational drives—such as curiosity, boredom, and novelty—to foster truly autonomous, adaptive behavior without explicit external commands. This approach, rooted in cognitive and neuroscientific principles, enables robots to self-direct exploration and learning, moving beyond traditional task-specific programming. In a related study on “Classification and Novelty Detection of Omni-view Images Taken from a Mobile Robot” (2009, 3 citations), Kiriake further advances robot perception by developing methods for recognizing and responding to novel visual environments. Though her citation counts are modest, her work is pioneering in its integration of intrinsic motivation into reinforcement learning, offering a foundational perspective for researchers in developmental robotics and embodied AI. Kiriake’s contributions are particularly notable for their early vision of machines that learn and behave with a sense of internal purpose, a concept now central to modern autonomous systems.
Research Focus
Key Achievements
Top Papers
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