A reinforcement learning agent uses local activity fields to steer active nematic defects along designer trajectories such as overdamped springs, with only coarse, low-dimensional feedback.
Topological defects in the nematic order of actin fibres as organization centres of hydra morphogenesis
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Tailoring interactions between active nematic defects with reinforcement learning
A reinforcement learning agent uses local activity fields to steer active nematic defects along designer trajectories such as overdamped springs, with only coarse, low-dimensional feedback.