class_docstr: Agent that selects action uniformly randomly.
docstr: Observe one transition and choose an action.
code: def step(self, reward, next_state):
      """Observe one transition and choose an action."""
      self.step_count += 1
      action, _ = self._choose_action(next_state)
      return action, {}
  
file_path: CNTK/bindings/python/cntk/contrib/deeprl/agent/random_agent.py
imports: import numpy
  from .agent import AgentBaseClass
label_desc: Use image node_id 3 for calling the RandomAgent obj's underlying member method code with example usage: obj.step(reward, next_state) and returns: action,  dict