(self, action, resolving_leap_bonus=5.0,
                          leaping_twice_punishment=-5.0)
Applies punishment and reward based on the principle leap up leap back.

    Large interval jumps (more than a fifth) should be followed by moving back
    in the same direction.

    Args:
      action: One-hot encoding of the chosen action.
      resolving_leap_bonus: Amount of reward dispensed for resolving a previous
        leap.
      leaping_twice_punishment: Amount of reward received for leaping twice in
        the same direction.
    Returns:
      Float reward value.
Applies punishment and reward based on the principle leap up leap back.
Applies punishment and reward based on the principle leap up leap back .
def reward_leap_up_back(self, action, resolving_leap_bonus=5.0,
                          leaping_twice_punishment=-5.0):
    """Applies punishment and reward based on the principle leap up leap back.

    Large interval jumps (more than a fifth) should be followed by moving back
    in the same direction.

    Args:
      action: One-hot encoding of the chosen action.
      resolving_leap_bonus: Amount of reward dispensed for resolving a previous
        leap.
      leaping_twice_punishment: Amount of reward received for leaping twice in
        the same direction.
    Returns:
      Float reward value.
    """

    leap_outcome = self.detect_leap_up_back(action)
    if leap_outcome == rl_tuner_ops.LEAP_RESOLVED:
      tf.logging.debug('Leap resolved, awarding %s', resolving_leap_bonus)
      return resolving_leap_bonus
    elif leap_outcome == rl_tuner_ops.LEAP_DOUBLED:
      tf.logging.debug('Leap doubled, awarding %s', leaping_twice_punishment)
      return leaping_twice_punishment
    else:
      return 0.0
def reward_leap_up_back ( self , action , resolving_leap_bonus = 5.0 , leaping_twice_punishment = - 5.0 ) : leap_outcome = self . detect_leap_up_back ( action ) if leap_outcome == rl_tuner_ops . LEAP_RESOLVED : tf . logging . debug ( 'Leap resolved, awarding %s' , resolving_leap_bonus ) return resolving_leap_bonus elif leap_outcome == rl_tuner_ops . LEAP_DOUBLED : tf . logging . debug ( 'Leap doubled, awarding %s' , leaping_twice_punishment ) return leaping_twice_punishment else : return 0.0