class_docstr: Does as little as possible, returns random actions
  
  :param observation_space: The observation space for the environment (in the state to observation interface)
code: def __init__(self, observation_space: gym.spaces.space.Space):
      super().__init__()
  
      self.pubsub = Pubsub(self.context.event_service)
      self.dummy_core_events = self.pubsub.create_event_topic(
          DummyEnvEvents
      )
  
      self.reward_aggregator = RewardAggregator()
      self.pubsub.register_subscriber(self.reward_aggregator)
  
      self.observation_space = observation_space
  
      # initialize rendering
      self.renderer = DummyMatplotlibRenderer()
  
imports: from typing import Tuple, Dict, Any, Optional
  import gym
  import numpy
  from maze.core.env.core_env import CoreEnv
  from maze.core.env.structured_env import StepKeyType, ActorID
  from maze.core.events.pubsub import Pubsub
  from maze.core.rendering.renderer import Renderer
  from maze.test.shared_test_utils.dummy_env.dummy_renderer import DummyMatplotlibRenderer
  from maze.test.shared_test_utils.dummy_env.reward.base import RewardAggregator, DummyEnvEvents
label_desc: Use image node_id 1 to create a new DummyCoreEnvironment object from inherited base classes: CoreEnv with example: obj = DummyCoreEnvironment(observation_space)