  MicroRacer is a simple, open source environment inspired by car racing
especially meant for the didactics of Deep Reinforcement Learning. The
complexity of the environment has been explicitly calibrated to allow users to
experiment with many different methods, networks and hyperparameters settings
without requiring sophisticated software or the need of exceedingly long
training times. Baseline agents for major learning algorithms such as DDPG,
PPO, SAC, TD2 and DSAC are provided too, along with a preliminary comparison in
terms of training time and performance.
