from rl_coach.agents.actor_critic_agent import ActorCriticAgentParameters from rl_coach.architectures.middleware_parameters import LSTMMiddlewareParameters from rl_coach.base_parameters import VisualizationParameters, MiddlewareScheme, PresetValidationParameters from rl_coach.core_types import TrainingSteps, EnvironmentEpisodes, EnvironmentSteps from rl_coach.environments.environment import SingleLevelSelection from rl_coach.environments.gym_environment import Atari, atari_deterministic_v4 from rl_coach.graph_managers.basic_rl_graph_manager import BasicRLGraphManager from rl_coach.graph_managers.graph_manager import ScheduleParameters #################### # Graph Scheduling # #################### schedule_params = ScheduleParameters() schedule_params.improve_steps = TrainingSteps(10000000000) schedule_params.steps_between_evaluation_periods = EnvironmentEpisodes(100) schedule_params.evaluation_steps = EnvironmentEpisodes(3) schedule_params.heatup_steps = EnvironmentSteps(10000) ######### # Agent # ######### agent_params = ActorCriticAgentParameters() agent_params.algorithm.apply_gradients_every_x_episodes = 1 agent_params.algorithm.num_steps_between_gradient_updates = 20 agent_params.algorithm.beta_entropy = 0.05 agent_params.network_wrappers['main'].learning_rate = 0.0001 agent_params.network_wrappers['main'].middleware_parameters = LSTMMiddlewareParameters(scheme=MiddlewareScheme.Medium, number_of_lstm_cells=256) ############### # Environment # ############### env_params = Atari(level=SingleLevelSelection(atari_deterministic_v4)) ######## # Test # ######## preset_validation_params = PresetValidationParameters() preset_validation_params.trace_test_levels = ['breakout', 'pong', 'space_invaders'] graph_manager = BasicRLGraphManager(agent_params=agent_params, env_params=env_params, schedule_params=schedule_params, vis_params=VisualizationParameters(), preset_validation_params=preset_validation_params)