code: def updateQTableFromTerminatingState( self, reward ):
          
          
          # retrieve the old action value from the Q-table (indexed by the previous state and the previous action)
          old_q = self.q_table[self.prev_s][self.prev_a]
          
          # TODO: what should the new action value be?
          new_q = old_q
          
          # assign the new action value to the Q-table
          self.q_table[self.prev_s][self.prev_a] = new_q
docs: Change q_table to reflect what we have learnt, after reaching a terminal state.