Smart GridWorldSim using actors and automated step processing

[rusu24edward]

In #72 we automated the observers, states, and dones, but we did not do actors because the step function cannot be easily consolidated into a simple format. After we do #337, we should have a better idea of how to streamline the action processing.

    # Note: This is the theoretical approach we could take in stepping the simulation.
    # The first 4 lines are boilerplate and good to have in this super class.
    # After that, the result is unique to the actor. The output may be different, and
    # what the simulation should do with that output is also different. This
    # could be streamlined after we do #337. For now, we leave it up to the subclass
    # to implement the actors and step function.
    # def step(self, action_dict, **kwargs):
    #     if not self._warning_issued:
    #         raise UserWarning("It is best practice to implement your own step function.")
    #     for actor in self._actors:
    #         for agent_id, action in action_dict.items():
    #             agent = self.agents[agent_id]
    #             if agent.active:
    #                 result = actor.process_action(agent, action, **kwargs)
    #                 if result: # Positive result
    #                     self.rewards[agent_id] += 1
    #                 else:
    #                     self.rewards[agent_id] -= 0.1

    #     for agent_id in action_dict:
    #         self.rewards[agent_id] -= 0.01

To be done after #337