Learning to control active matter

Learning to control active matter

Blog Article

The study of active matter has revealed novel non-equilibrium collective behaviors, illustrating their potential as a new materials platform.However, most work treat active matter as unregulated systems with uniform microscopic energy input, which we refer to as activity.In contrast, functionality in biological materials results from regulating and controlling activity locally over space and time, as has only recently become experimentally possible for engineered active matter.

Designing functionality requires Short- and long-term habituation of auditory event-related potentials in the rat [v1; ref status: indexed, http://f1000r.es/1l3] navigation of the high-dimensional space of spatio-temporal activity patterns, but brute force approaches are unlikely to be successful without system-specific intuition.Here, we apply reinforcement learning to the task of inducing net transport in a specific direction for a simulated system of Vicsek-like self-propelled disks using a spotlight that increases activity locally.The resulting time-varying patterns of activity Comparison of effects of spatial anticrime in open communities in China learned exploit the distinct physics of the strong and weak coupling regimes.

Our work shows how reinforcement learning can reveal physically interpretable protocols for controlling collective behavior in non-equilibrium systems.