ray.rllib.algorithms.algorithm_config.AlgorithmConfig.build

AlgorithmConfig.build(env: str | Any | gymnasium.Env | None = None, logger_creator: Callable[[], Logger] | None = None, use_copy: bool = True) → Algorithm

Builds an Algorithm from this AlgorithmConfig (or a copy thereof).

Parameters:

• env – Name of the environment to use (e.g. a gym-registered str), a full class path (e.g. “ray.rllib.examples.envs.classes.random_env.RandomEnv”), or an Env class directly. Note that this arg can also be specified via the “env” key in config.

• logger_creator – Callable that creates a ray.tune.Logger object. If unspecified, a default logger is created.

• use_copy – Whether to deepcopy self and pass the copy to the Algorithm (instead of self) as config. This is useful in case you would like to recycle the same AlgorithmConfig over and over, e.g. in a test case, in which we loop over different DL-frameworks.

Returns:

A ray.rllib.algorithms.algorithm.Algorithm object.