def __init__(self):
super().__init__(
algorithm=SILAlgorithmParameters(),
exploration=
None, #TODO this should be different for continuous (ContinuousEntropyExploration)
# and discrete (CategoricalExploration) action spaces. how to deal with that?
memory=PrioritizedExperienceReplayParameters(),
networks={"main": SILNetworkParameters()})
def __init__(self):
super().__init__()
self.algorithm = RainbowDQNAlgorithmParameters()
# ParameterNoiseParameters is changing the network wrapper parameters. This line needs to be done first.
self.network_wrappers = {"main": RainbowDQNNetworkParameters()}
self.exploration = ParameterNoiseParameters(self)
self.memory = PrioritizedExperienceReplayParameters()
def __init__(self):
super().__init__()
self.algorithm = RainbowDQNAlgorithmParameters()
self.exploration = ParameterNoiseParameters(self)
self.memory = PrioritizedExperienceReplayParameters()
self.network_wrappers = {"main": RainbowDQNNetworkParameters()}
from rl_coach.agents.ddqn_agent import DDQNAgentParameters
from rl_coach.base_parameters import VisualizationParameters, PresetValidationParameters
from rl_coach.environments.environment import SingleLevelSelection
from rl_coach.environments.gym_environment import Atari, atari_deterministic_v4, atari_schedule
from rl_coach.graph_managers.basic_rl_graph_manager import BasicRLGraphManager
from rl_coach.memories.non_episodic.prioritized_experience_replay import PrioritizedExperienceReplayParameters
from rl_coach.schedules import LinearSchedule
#########
# Agent #
#########
agent_params = DDQNAgentParameters()
agent_params.network_wrappers['main'].learning_rate = 0.00025 / 4
agent_params.memory = PrioritizedExperienceReplayParameters()
agent_params.memory.beta = LinearSchedule(
0.4, 1, 12500000) # 12.5M training iterations = 50M steps = 200M frames
###############
# 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(