  An innovative scheme is proposed for the dynamic control of phase in
two-dimensional laser beam array. It is based on a simple neural network that
predicts the complex field array from the intensity of the induced scattered
pattern through a phase intensity transformer made of a diffuser. Iterated
phase corrections are applied on the laser field array by phase modulators via
a feedback loop to set the array to prescribed phase values. A crucial feature
is the use of a kind of reinforcement learning approach for the neural network
training which takes account of the iterated corrections. Experiments on a
proof of concept system demonstrated the high performance and scalability of
the scheme with an array of up to 100 laser beams and a phase setting at 1/30
of the wavelength.
