'''This module defines the concrete classes for training'''
from markov.agent_ctrl.utils import load_action_space
from markov.agent_ctrl.agent_ctrl_interface import AgentCtrlInterface

class TrainingCtrl(AgentCtrlInterface):
    '''Concrete class for an agent that drives forward'''
    def __init__(self, agent_name, model_metadata):
        """constructor for the training agent ctrl

        Args:
            agent_name (str): name of the agent
            model_metadata (ModelMetadata): object containing the details in the model metadata json file
        """
        # Store the name of the agent used to set agents position on the track
        self._agent_name_ = agent_name
        #Create default reward parameters
        self._action_space_ = load_action_space(model_metadata)
        self._model_metadata_ = model_metadata

    @property
    def action_space(self):
        return self._action_space_

    @property
    def model_metadata(self):
        return self._model_metadata_

    def reset_agent(self):
        pass

    def send_action(self, action):
        pass

    def update_agent(self, action):
        return {}

    def judge_action(self, agents_info_map):
        return None, None, None

    def finish_episode(self):
        pass