text: from rl_coach.agents.dfp_agent import DFPAgentParameters
  from rl_coach.memories.memory import MemoryGranularity
  
  from rl_coach.memories.non_episodic import ExperienceReplayParameters
  
  from rl_coach.exploration_policies.e_greedy import EGreedyParameters
  
  from rl_coach.agents.dqn_agent import DQNAgentParameters, DQNAlgorithmParameters, DQNNetworkParameters
  
  from rl_coach.agents.rainbow_dqn_agent import RainbowDQNAgentParameters
  from rl_coach.base_parameters import PresetValidationParameters, VisualizationParameters, AgentParameters
  from rl_coach.core_types import EnvironmentSteps
  from rl_coach.environments.second_test import ControlSuiteEnvironmentParameters
  from rl_coach.graph_managers.basic_rl_graph_manager import BasicRLGraphManager
  from rl_coach.graph_managers.graph_manager import SimpleSchedule
  
  experience_replay_parameters = ExperienceReplayParameters()
  experience_replay_parameters.max_size = (MemoryGranularity.Transitions, 10000)
  agent_params = DFPAgentParameters()
  agent_params.memory = experience_replay_parameters
  schedule_params = SimpleSchedule()
  schedule_params.heatup_steps = EnvironmentSteps(10)
  preset_validation_params = PresetValidationParameters(test=True, min_reward_threshold=-50000, max_episodes_to_achieve_reward=10, num_workers=5)
  vis_params = VisualizationParameters(render=False)
  
  env_params = ControlSuiteEnvironmentParameters()
  graph_manager = BasicRLGraphManager(agent_params=agent_params, env_params=env_params,
                                      schedule_params=schedule_params, vis_params=VisualizationParameters(),
                                      preset_validation_params=preset_validation_params)
  