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rainbow dqn hyper-parameter updates

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Gal Leibovich
2018-08-30 20:41:33 +03:00
parent 07db625987
commit d862a3be83
2 changed files with 18 additions and 9 deletions
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14
rl_coach/presets/Atari_Rainbow.py
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@@ -1,4 +1,3 @@
from rl_coach.agents.categorical_dqn_agent import CategoricalDQNAgentParameters
from rl_coach.agents.rainbow_dqn_agent import RainbowDQNAgentParameters
from rl_coach.base_parameters import VisualizationParameters, PresetValidationParameters
from rl_coach.core_types import EnvironmentSteps, RunPhase
@@ -13,17 +12,20 @@ from rl_coach.schedules import LinearSchedule
####################
schedule_params = ScheduleParameters()
schedule_params.improve_steps = EnvironmentSteps(50000000)
schedule_params.steps_between_evaluation_periods = EnvironmentSteps(250000)
schedule_params.evaluation_steps = EnvironmentSteps(135000)
schedule_params.heatup_steps = EnvironmentSteps(50000)
schedule_params.steps_between_evaluation_periods = EnvironmentSteps(1000000)
schedule_params.evaluation_steps = EnvironmentSteps(125000)
schedule_params.heatup_steps = EnvironmentSteps(20000)
#########
# Agent #
#########
agent_params = RainbowDQNAgentParameters()
agent_params.network_wrappers['main'].learning_rate = 0.00025
agent_params.memory.beta = LinearSchedule(0.4, 1, 12500000) # 12.5M training iterations = 50M steps = 200M frames
agent_params.network_wrappers['main'].learning_rate = 0.0000625
agent_params.network_wrappers['main'].optimizer_epsilon = 1.5e-4
agent_params.algorithm.num_steps_between_copying_online_weights_to_target = EnvironmentSteps(32000 // 4) # 32k frames
agent_params.memory.beta = LinearSchedule(0.4, 1, 12500000) # 12.5M training iterations = 50M steps = 200M frames
agent_params.memory.alpha = 0.5
###############
# Environment #