def average_fitness_termination(population, num_generations, num_evaluations, args):
    """Return True if the population's average fitness is near its best fitness.
    
    This function calculates the average fitness of the population, as well
    as the best fitness. If the difference between those values is less 
    than a specified tolerance, the function returns True. 
    
    .. Arguments:
       population -- the population of Individuals
       num_generations -- the number of elapsed generations
       num_evaluations -- the number of candidate solution evaluations
       args -- a dictionary of keyword arguments
    
    Optional keyword arguments in args:
    
    - *tolerance* -- the minimum allowable difference between average 
      and best fitness (default 0.001)
    
    """
    tolerance = args.setdefault('tolerance', 0.001)
    avg_fit = sum([x.fitness for x in population]) / float(len(population))
    best_fit = max([x.fitness for x in population])
    return (best_fit - avg_fit) < tolerance
Return True if the population's average fitness is near its best fitness.
    
    This function calculates the average fitness of the population, as well
    as the best fitness. If the difference between those values is less 
    than a specified tolerance, the function returns True. 
    
    .. Arguments:
       population -- the population of Individuals
       num_generations -- the number of elapsed generations
       num_evaluations -- the number of candidate solution evaluations
       args -- a dictionary of keyword arguments
    
    Optional keyword arguments in args:
    
    - *tolerance* -- the minimum allowable difference between average 
      and best fitness (default 0.001)