Genetic Algorithms ( Artificial Intelligence )

Genetic Algorithm steps:-

 

Genetic Algorithm flow chart.

(1) [Start]  Generate random population of  n chromosomes (Encode suitable solutions for the problem).
(2)  [Fitness]  Evaluate the fitness  f(x) of each chromosome x in the population.

(3) [New population]  Create a new population by repeating following steps until the new population is complete.

• [Selection]  Select two parent chromosomes from a population according to their fitness.
• [Crossover] With a crossover probability, cross over the parents to form new offspring (children).  If no crossover is performed, the offspring would be the exact copy of parents. 
• [Mutation] With a mutation probability, mutate the new offspring at each locus (position in chromosome).
• [Accepting] Place new offspring in the new population.

(4)  [Replace]  Use new generated population for a further run of the algorithm.

(5) [Test]  If the end condition is satisfied, stop, and return the best solution in the current population.
(6)  [Loop] Go to step 2. 

■  Genetic Algorithms does unsupervised learning - the right answer is not known beforehand.