Reward shaping is a well-established family of techniques
that have been successfully used to improve the performance
and learning speed of Reinforcement Learning agents in singleobjective
problems. Here we extend the guarantees of Potential-
Based Reward Shaping (PBRS) by providing theoretical
proof that PBRS does not alter the true Pareto front in
MORL domains. We also contribute the rst empirical studies
of the e ect of PBRS in MORL problems.