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Overview of RLGym

RLGym breaks down a reinforcement learning environment into a set of components, which we call "configuration objects." Every environment is defined by a set of these objects, and the RLGym API handles the flow of information between them to present a consistent interface for an agent to interact with. To create a new environment, users just need to implement each of the configuration objects described below and pass them to the RLGym constructor.

Configuration Objects​

There are a total of 6 required configuration objects, and an optional renderer. They are:

  • A TransitionEngine: Handles how the environment changes from one state to another
  • A StateMutator: Controls how the environment gets reset or modified
  • An ObsBuilder: Turns the environment state into agent observations
  • An ActionParser: Defines what actions agents can take
  • A RewardFunction: Determines what rewards agents receive
  • One or more DoneConditions: Decide when episodes should be terminated (natural end) or truncated (early stop)
  • Optionally a Renderer: Shows you what's happening in the environment

The diagram below shows the interaction between these components:

To see an example of a concrete implementation of these configuration objects, see our Custom Environment guide, or check out the individual examples relevant to Rocket League in our Rocket League section.