text: from environments import FrozenLakeEnv
  from agents import DPAgent
  
  """
  The following is a showcase for the dynamic programming agent to solve the frozen lake. 
  """
  
  env = FrozenLakeEnv()
  dp_agent = DPAgent(env, theta=0.005)
  max_steps = 150
  
  reward_sum = 0
  iterations = 100
  for _ in range(iterations):
      state = env.reset()
      done = False
      while not done:
          action = dp_agent.act(state)
          state, reward, done, _ = env.step(action)
          reward_sum += reward
  
  print(f'Dynamic Programming Agent solved {round(reward_sum / iterations, 2) * 100}% of FrozenLake4x4 iterations')
  