After training, the aim is to execute, zero-shot, novel instructions such as "walk around right after look twice." Previous studies show that seq2seq recurrent neural networks (RNN) generalize well when the training and test sets are similar, but fail catastrophically when generalization requires systematic compositionality<cite> [15,</cite> 3, 20] .