Our experiments show that interleaving behavioral cloning and policy gradient training phases improves performance on the validation set.
we interleaved each policy gradient update batch with K behaviour cloning batches, with the value of K decaying exponentially, such that the training strategy asymptotically becomes only policy gradient updates.