A question about the step function

Assuming that the current state is s0, what should I do when I only want to get the latter states s1 s2 and don't push the agent to these states in fact? I think that this operation is simlilar to the Monte Carlo Tree Search in AlphaGo. However, I can't solve this problem myself. I sincerely ask for your help.
eg:
import deepmind_lab
env = deepmind_lab.Lab(level_name, observation_format, string_args, renderer)
reward=env.step()
In fact, I can't find the step function. So I can't try to add a new function which can return the next state.