Holographic Recurrent Networks (HRNs) are recurrent networks which incorporate associative memory techniques for storing se(cid:173) quential structure. HRNs can be easily and quickly trained using gradient descent techniques to generate sequences of discrete out(cid:173) puts and trajectories through continuous spaee. The performance of HRNs is found to be superior to that of ordinary recurrent net(cid:173) works on these sequence generation tasks.