Learning comparison: Reinforcement Learning vs Inverse Reinforcement Learning : How well does inverse reinforcement learning perform in simple markov decision processes in comparison to reinforcement learning?

Abstract: This research project elaborates a qualitative comparison between two different learning approaches, Reinforcement Learning (RL) and Inverse Reinforcement Learning (IRL) over the Gridworld Markov Decision Process. The interest focus will be set on the second learning paradigm, IRL, as it is considered to be relatively new and little work has been developed in this field of study. As observed, RL outperforms IRL, obtaining a correct solution in all the different scenarios studied. However, the behaviour of the IRL algorithms can be improved and this will be shown and analyzed as part of the scope.