I would like to have a simple explanation of the differences between genetic algorithms and genetic programming (without too much programming jargon). Examples would also be appreciated.
Apparently, in genetic programming, solutions are computer programs. On the other hand, genetic algorithms represent a solution as a string of numbers. Any other differences?
Lots of good partial answers above. As Koza put it in his seminal texts on the subject, "[if a GA was the best solution for a problem then a GP would evolve a GA to solve it]." Simply put, a GP is a type of GA that evolves programs that are evaluated by a cost function. The fact that the genome is a program rather than a collection of inputs for the cost function IMHO is the material difference.
genetic programming is much more powerful than genetic algorithms. the output of the genetic algorithms is a quantity while the output of the genetic programming is another computer program.
