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53 lines
2.1 KiB
Python
53 lines
2.1 KiB
Python
from rl_coach.agents.dfp_agent import DFPAgentParameters, HandlingTargetsAfterEpisodeEnd
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from rl_coach.base_parameters import VisualizationParameters, PresetValidationParameters
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from rl_coach.core_types import TrainingSteps, EnvironmentEpisodes, EnvironmentSteps
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from rl_coach.environments.doom_environment import DoomEnvironmentParameters
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from rl_coach.graph_managers.basic_rl_graph_manager import BasicRLGraphManager
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from rl_coach.graph_managers.graph_manager import ScheduleParameters
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from rl_coach.schedules import LinearSchedule
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####################
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# Graph Scheduling #
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####################
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schedule_params = ScheduleParameters()
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schedule_params.improve_steps = TrainingSteps(10000000000)
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schedule_params.steps_between_evaluation_periods = EnvironmentEpisodes(50)
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schedule_params.evaluation_steps = EnvironmentEpisodes(3)
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# There is no heatup for DFP. heatup length is determined according to batch size. See below.
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#########
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# Agent #
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#########
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agent_params = DFPAgentParameters()
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schedule_params.heatup_steps = EnvironmentSteps(agent_params.network_wrappers['main'].batch_size)
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agent_params.network_wrappers['main'].learning_rate = 0.0001
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agent_params.exploration.epsilon_schedule = LinearSchedule(0.5, 0, 10000)
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agent_params.exploration.evaluation_epsilon = 0
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# this works better than the default which is 64
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agent_params.algorithm.num_consecutive_playing_steps = EnvironmentSteps(1)
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agent_params.algorithm.use_accumulated_reward_as_measurement = True
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agent_params.algorithm.goal_vector = [0, 1] # ammo, accumulated_reward
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agent_params.algorithm.handling_targets_after_episode_end = HandlingTargetsAfterEpisodeEnd.LastStep
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###############
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# Environment #
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###############
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env_params = DoomEnvironmentParameters(level='basic')
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########
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# Test #
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########
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preset_validation_params = PresetValidationParameters()
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preset_validation_params.trace_max_env_steps = 2000
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graph_manager = BasicRLGraphManager(agent_params=agent_params, env_params=env_params,
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schedule_params=schedule_params, vis_params=VisualizationParameters(),
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preset_validation_params=preset_validation_params)
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