PQLRM is a multi-objective reinforcement learning algorithm that combines Pareto Q-Learning with Reward Machines to handle non-Markovian rewards. It converges faster than a naive PQL baseline on cross-product MDPs and generates Pareto-optimal policies beyond the capability of QRM.