(n, total, p_initial, p_final)
Linearly interpolates a probability between p_initial and p_final.

  Current probability is based on the current step, n. Used to linearly anneal
  the exploration probability of the RLTuner.

  Args:
    n: The current step.
    total: The total number of steps that will be taken (usually the length of
      the exploration period).
    p_initial: The initial probability.
    p_final: The final probability.

  Returns:
    The current probability (between p_initial and p_final).
Linearly interpolates a probability between p_initial and p_final.
Linearly interpolates a probability between p_initial and p_final .
def linear_annealing(n, total, p_initial, p_final):
  """Linearly interpolates a probability between p_initial and p_final.

  Current probability is based on the current step, n. Used to linearly anneal
  the exploration probability of the RLTuner.

  Args:
    n: The current step.
    total: The total number of steps that will be taken (usually the length of
      the exploration period).
    p_initial: The initial probability.
    p_final: The final probability.

  Returns:
    The current probability (between p_initial and p_final).
  """
  if n >= total:
    return p_final
  else:
    return p_initial - (n * (p_initial - p_final)) / (total)
def linear_annealing ( n , total , p_initial , p_final ) : if n >= total : return p_final else : return p_initial - ( n * ( p_initial - p_final ) ) / ( total )