No title
The success of Reinforcement Learning (RL) has mostly been in artificial domains, with only some successful real-world applications. One of the reasons being that most real-world domains fail to satisfy a set of assumptions of RL theory. In the past years, a popular way to gauge the performance of RL agents has been through a suite of Atari 2600 games. This suite has been used to benchmark the pr
