  In this paper, we consider the optimal control of material micro-structures.
Such material micro-structures are modeled by the so-called phase field model.
We study the underlying physical structure of the model and propose a data
based approach for its optimal control, along with a comparison to the control
using a state of the art Reinforcement Learning (RL) algorithm. Simulation
results show the feasibility of optimally controlling such micro-structures to
attain desired material properties and complex target micro-structures.

Systems and Control;Systems and Control