  Multi-layer optical film has been found to afford important applications in
optical communication, optical absorbers, optical filters, etc. Different
algorithms of multi-layer optical film design has been developed, as simplex
method, colony algorithm, genetic algorithm. These algorithms rapidly promote
the design and manufacture of multi-layer films. However, traditional numerical
algorithms of converge to local optimum. This means that the algorithms can not
give a global optimal solution to the material researchers. In recent years,
due to the rapid development to far artificial intelligence, to optimize
optical film structure using AI algorithm has become possible. In this paper,
we will introduce a new optical film design algorithm based on the deep Q
learning. This model can converge the global optimum of the optical thin film
structure, this will greatly improve the design efficiency of multi-layer
films.
