toolbox register("individual"tools inititeratecreator individualtoolbox exprtoolbox register("population",tools initrepeat,listtoolbox individualtoolbox register("compile"gp compilepset=psettoolbox register("evaluate"eval_funcpoints=[ / for in range( , )]toolbox register("select"tools seltournamenttournsize= toolbox register("mate"gp cxonepointtoolbox register("expr_mut"gp genfullmin_= max_= toolbox register("mutate"gp mutuniformexpr=toolbox expr_mutpset=psettoolbox decorate("mate"gp staticlimit(key=operator attrgetter("height")max_value= )toolbox decorate("mutate"gp staticlimit(key=operator attrgetter("height")max_value= )return toolbox if __name__ ="__main__"random seed( toolbox create_toolbox(population toolbox population( = hall_of_fame tools halloffame( stats_fit tools statistics(lambda xx fitness valuesstats_size tools statistics(lenmstats tools multistatistics(fitness=stats_fitsize=stats_sizemstats register("avg"np meanmstats register("std"np stdmstats register("min"np minmstats register("max"np maxprobab_crossover probab_mutate number_gen populationlog algorithms easimple(populationtoolboxprobab_crossoverprobab_mutatenumber_genstats=mstatshalloffame=hall_of_fameverbose=truenote that all the basic steps are same as used while generating bit patterns this program will give us the output as minmaxstd (standard deviationafter number of generations