class_docstr: Single-agent gym-like environment based on a multi-agent environment for which
  all but one agent has been fixed.
class_docstr_tok: ["Single-agent","gym-like","environment","based","on","a","multi-agent","environment","for","which","all","but","one","agent","has","been","fixed","."]
code: def step(
      self, action: tp.Any
  ) -> tp.Tuple[tp.Any, tp.Any, bool, tp.Dict[tp.Any, tp.Any]]:
      an = self._agent_name
      obs, reward, done, info = self.env.step({an: action})
      return (
          obs[an],
          reward[an],
          done[an] | done["__all__"],
          info.get(an, {}),
      )
  
imports: import typing
  from collections import defaultdict
  import gym
label_desc: Use image node_id 3 for calling the SingleAgentEnv obj's underlying member method code with example usage: obj.step(action) and returns: obs,  reward,  unknown,  info