  Genetic algorithms are considered as one of the most efficient search
techniques. Although they do not offer an optimal solution, their ability to
reach a suitable solution in considerably short time gives them their
respectable role in many AI techniques. This work introduces genetic algorithms
and describes their characteristics. Then a novel method using genetic
algorithm in best training set generation and selection for a back-propagation
network is proposed. This work also offers a new extension to the original
genetic algorithms
