code: def observe_reward_value(self, state_key, action_key):
          '''
          Compute the reward value.
          
          Args:
              state_key:              The key of state.
              action_key:             The key of action.
          
          Returns:
              Reward value.
  
          '''
          x, y = state_key
  
          if self.__map_arr[y][x] == self.__end_point_label:
              return 100.0
          elif self.__map_arr[y][x] == self.__start_point_label:
              return 0.0
          elif self.__map_arr[y][x] == self.__wall_label:
              raise ValueError("It is the wall. (x, y)=(%d, %d)" % (x, y))
          else:
              reward_value = float(self.__map_arr[y][x])
              self.save_r_df(state_key, reward_value)
              return reward_valuf observe_reward_value(self, state_key, action_key):
          '''
          Compute the reward value.
          
          Args:
              state_key:              The key of state.
              action_key:             The key of action.
          
          Returns:
              Reward value.
  
          '''
          x, y = state_key
  
          if self.__map_arr[y][x] == self.__end_point_label:
              return 100.0
          elif self.__map_arr[y][x] == self.__start_point_label:
              return 0.0
          elif self.__map_arr[y][x] == self.__wall_label:
              raise ValueError("It is the wall. (x, y)=(%d, %d)" % (x, y))
          else:
              reward_value = float(self.__map_arr[y][x])
              self.save_r_df(state_key, reward_value)
              return reward_value
docs: Compute the reward value.
          
          Args:
              state_key:              The key of state.
              action_key:             The key of action.
          
          Returns:
              Reward value.