csle_agents.agents.ppg_clean package

Submodules

csle_agents.agents.ppg_clean.ppg_clean_agent module

MIT License

Copyright (c) 2019 CleanRL developers https://github.com/vwxyzjn/cleanrl

class csle_agents.agents.ppg_clean.ppg_clean_agent.PPGCleanAgent(simulation_env_config: SimulationEnvConfig, emulation_env_config: Union[None, EmulationEnvConfig], experiment_config: ExperimentConfig, training_job: Optional[TrainingJobConfig] = None, save_to_metastore: bool = True)[source]

Bases: BaseAgent

A Phasic Policy Gradient agent using the implementation from CleanRL

hparam_names() List[str][source]
Returns

a list with the hyperparameter names

make_env() Callable[[], RecordEpisodeStatistics[Any, Any]][source]

Helper function for creating the environment to use for training

Returns

a function that creates the environment

run_ppg(exp_result: ExperimentResult, seed: int) Tuple[ExperimentResult, BaseEnv, PPONetwork][source]

Runs PPG with a given seed

Parameters
  • exp_result – the object to save the experiment results

  • seed – the random seed

Returns

the updated experiment results, the environment, and the trained model

train() ExperimentExecution[source]

Runs the training process

Returns

the results

Module contents