  In recent years, Reinforcement Learning (RL), has become a popular field of
study as well as a tool for enterprises working on cutting-edge artificial
intelligence research. To this end, many researchers have built RL frameworks
such as openAI Gym and KerasRL for ease of use. While these works have made
great strides towards bringing down the barrier of entry for those new to RL,
we propose a much simpler framework called EasyRL, by providing an interactive
graphical user interface for users to train and evaluate RL agents. As it is
entirely graphical, EasyRL does not require programming knowledge for training
and testing simple built-in RL agents. EasyRL also supports custom RL agents
and environments, which can be highly beneficial for RL researchers in
evaluating and comparing their RL models.
