code: def is_on_policy(self) -> bool:
      return False
  
file_path: coach/rl_coach/agents/mmc_agent.py
imports: from typing import Union
  import numpy
  from rl_coach.agents.dqn_agent import DQNAgentParameters, DQNAlgorithmParameters
  from rl_coach.agents.value_optimization_agent import ValueOptimizationAgent
  from rl_coach.memories.episodic.episodic_experience_replay import EpisodicExperienceReplayParameters
label_desc: Use image node_id 2 for calling the MixedMonteCarloAgent obj's underlying member method code with example usage: obj.is_on_policy() and returns: False