title: How to set a openai-gym environment start with a specific state not the `env.reset()`?
body: <p>Today, when I was trying to implement an rl-agent under the environment openai-gym, I found a problem that it seemed that all agents are trained from the most initial state: <code>env.reset()</code>, i.e.  </p>
  
  <pre class="lang-py prettyprint-override"><code>import gym
  
  env = gym.make("CartPole-v0")
  initial_observation = env.reset()  # &lt;-- Note
  done = False
  
  while not done:
      action = env.action_space.sample()  
      next_observation, reward, done, info = env.step(action)
  
  env.close()  # close the environment
  </code></pre>
  
  <p>So it is natural that the agent can behave down the route <code>env.reset() -(action)-&gt; next_state -(action)-&gt; next_state -(action)-&gt; ... -(action)-&gt; done</code>, this is an episode. But how can an agent start from a sepecific state like a middle state, then take an action from that state? For example, I sample an experience from the replay buffer, i.e. <code>(s, a, r, ns, done)</code>, what if I want train the agent start directly from the state <code>ns</code>, and get an action with a <code>Q-Network</code>, then for an <code>n-step</code> steps forward. Something like that:  </p>
  
  <pre class="lang-py prettyprint-override"><code>import gym
  
  env = gym.make("CartPole-v0")
  initial_observation = ns  # not env.reset() 
  done = False
  
  while not done:
      action = DQN(ns) 
      next_observation, reward, done, info = env.step(action)
      # n-step later or done is true, break
  
  env.close()  # close the environment
  </code></pre>
  
  <p>But even though I set a variable <code>initial_observation</code> as <code>ns</code>, I think the agent or the <code>env</code> will not aware it at all. How can I tell the <code>gym.env</code> that I want set the initial observation as <code>ns</code> and let the agent know the specific start state, get continue train directly from that specific observation(get start with that specific environment)?</p>