code: def no_improvement_termination(population, num_generations, num_evaluations, args):
      
      max_generations = args.setdefault('max_generations', 10)
      previous_best = args.setdefault('previous_best', None)
      current_best = max(population).fitness
      if previous_best is None or previous_best != current_best:
          args['previous_best'] = current_best
          args['generation_count'] = 0
          return False
      else:
          if args['generation_count'] >= max_generations:
              return True
          else:
              args['generation_count'] += 1
              return False
docs: Return True if the best fitness does not change for a number of generations.
      
      This function keeps track of the current best fitness and compares it to
      the best fitness in previous generations. Whenever those values are the 
      same, it begins a generation count. If that count exceeds a specified 
      number, the terminator 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:
      
      - *max_generations* -- the number of generations allowed for no change in fitness (default 10)