#################### # DQN Agent Params # #################### agent_params = DDQNAgentParameters() agent_params.network_wrappers['main'].learning_rate = 0.00025 agent_params.network_wrappers['main'].heads_parameters = [ DuelingQHeadParameters() ] agent_params.memory.max_size = (MemoryGranularity.Transitions, 1000000) agent_params.algorithm.discount = 0.99 agent_params.algorithm.num_consecutive_playing_steps = EnvironmentSteps(4) agent_params.exploration.epsilon_schedule = LinearSchedule( 1, 0.1, (N + 7) * 2000) agent_params.input_filter = NoInputFilter() agent_params.output_filter = NoOutputFilter() ############### # Environment # ############### env_params = GymEnvironmentParameters() env_params.level = 'rl_coach.environments.toy_problems.exploration_chain:ExplorationChain' env_params.additional_simulator_parameters = { 'chain_length': N, 'max_steps': N + 7 } vis_params = VisualizationParameters() # preset_validation_params = PresetValidationParameters() # preset_validation_params.test = True
agent_params.network_wrappers['main'].learning_rate = 0.0001 agent_params.network_wrappers['main'].input_embedders_parameters = { "screen": InputEmbedderParameters(input_rescaling={'image': 3.0}) } agent_params.network_wrappers['main'].heads_parameters = [ DuelingQHeadParameters() ] agent_params.memory.max_size = (MemoryGranularity.Transitions, 1000000) # slave_agent_params.algorithm.num_steps_between_copying_online_weights_to_target = EnvironmentSteps(10000) agent_params.exploration.epsilon_schedule = LinearSchedule(1.0, 0.1, 1000000) agent_params.algorithm.num_consecutive_playing_steps = EnvironmentSteps(4) agent_params.output_filter = \ OutputFilter( action_filters=OrderedDict([ ('discretization', BoxDiscretization(num_bins_per_dimension=4, force_int_bins=True)) ]), is_a_reference_filter=False ) ############### # Environment # ############### env_params = StarCraft2EnvironmentParameters(level='CollectMineralShards') env_params.feature_screen_maps_to_use = [5] env_params.feature_minimap_maps_to_use = [5] ######## # Test # ########