Momoko Watanabe

Rakuno Gakuen University, Toshiba (Japan)

Papers

Total Citations

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About

Momoko Watanabe is a researcher in robotics and multi-agent systems, with a focus on reinforcement learning and autonomous navigation. Her key contributions lie in developing algorithms that enable groups of robots to collaborate effectively on complex physical tasks. In her most cited work, "An Actor-Critic Approach for Learning Cooperative Behaviors of Multiagent Seesaw Balancing Problems" (2006, 3 citations), she pioneered a novel reinforcement learning framework that allows multiple autonomous mobile robots to learn coordinated behaviors without centralized control. This approach, tested on the challenging seesaw balancing task, demonstrated how agents could dynamically adapt their actions to achieve a shared goal. Watanabe also contributed to mobile robotics with her work on visual navigation systems (2005, 2 citations), addressing how robots can perceive and move through their environments. While her citation counts are modest, her research represents early and important steps toward scalable, decentralized multi-robot coordination—a foundation that has influenced subsequent work in cooperative robotics and distributed artificial intelligence.