  In this paper, we consider the recent trend of evaluating progress on
reinforcement learning technology by using text-based environments and games as
evaluation environments. This reliance on text brings advances in natural
language processing into the ambit of these agents, with a recurring thread
being the use of external knowledge to mimic and better human-level
performance. We present one such instantiation of agents that use commonsense
knowledge from ConceptNet to show promising performance on two text-based
environments.
