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20242026
most citedDeep Dive into Model-free Reinforcement Learning for Biological and Robotic Systems: Theory and Practice

3 citations · 3 across the 5 of their papers we have counts for

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Showing 2024Show all

2 papers · 1 filter

physics.flu-dyn2024

Hierarchical equivariant graph neural networks for forecasting collective motion in vortex clusters and microswimmers

Alec J. Linot, Haotian Hang, Eva Kanso +1

Data-driven modeling of collective dynamics is a challenging problem because emergent phenomena in multi-agent systems are often shaped by long-range interactions among individuals…

cs.RO2024★ 3 cited

Deep Dive into Model-free Reinforcement Learning for Biological and Robotic Systems: Theory and Practice

Yusheng Jiao, Feng Ling, Sina Heydari +3

Animals and robots exist in a physical world and must coordinate their bodies to achieve behavioral objectives. With recent developments in deep reinforcement learning, it is now p…