This paper explores the potentiality of pre-loading deep-Q learning agents’ replay memory buffers with experiences generated by preceding agents, so as to bolster their initial performance. The research illustrates that this pre-loading of previously generated experience replays does indeed improve the initial performance of new agents, provided that an appropriate degree of ostensibly undesirable activity was expressed in the preceding agent’s behaviour.