Author

Keisuke Okumura

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Preprint Oct 2026

Map-Distribution Mixture-of-Experts for Multi-Agent Pathfinding

This study explores a meta-level Mixture-of-Experts (MoE) approach to learning-based MAPF, where given a collection of compact yet high-performing experts specialised for different map distributions, the architecture learns a router that selectively fuses their outputs according to each agent's local situation.

Fumimaro Suzuki, Keisuke Okumura · 0 citations

Preprint Oct 2026

Learning Coordinated Visuomotor Box-Pushing from Solo Demonstrations

Multi-robot imitation learning, particularly in settings where visuomotor policies are deployed in a communication-free, onboard decentralised style, represents an attractive paradigm. However, its realisation remains insufficiently understood, largely due to the difficulty of collecting collective demonstrations, sinc...

Ryusei Matsumoto, Mei Kinjo, Yoko Sasaki et al. · 0 citations