Summary

In this chapter, we went through a custom Gym environment implementation step-by-step, starting with a template that laid out the bare-bones structure of an OpenAI Gym environment that provided all of the necessary interfaces to the agents. We also looked at how to register a custom environment implementation in the Gym registry so that we can use the familiar gym.make(ENV_NAME) command to create an instance of an existing environment. We then looked at how to create a Gym-compatible environment implementation for the UnrealEngine based on the open-source driving simulator, CARLA. We then quickly walked through the steps required to install and run CARLA and then started implementing the CarlaEnv class piece-by-piece, carefully covering all the important details involved in implementing custom environments compatible with OpenAI Gym.

In the next chapter, we will build an advanced agent from the ground up with hands-on examples, before eventually using the custom CARLA environment...