Using the link on Wikipedia, online learning "teaches one copy at a time." An online / offline label usually refers to how training data is fed into a controlled regression or classification algorithm. Because genetic programming is a heuristic search that uses an evaluation function to evaluate the suitability of its decisions, rather than a set of labeled workouts, these terms do not really apply.
If you ask if the result of the GP algorithm can be used (that is, the best phenotype), although it is still โlookingโ for the best solutions, I see no reason why not, assuming this makes sense for your domain / application . Once your GA / GP aggregate reaches a certain threshold, you can apply this solution to your application and continue working with GP, switching to a new solution when it becomes available.
One approach along this line is an algorithm called rtNEAT , which attempts to use the genetic algorithm to generate and update a neural network in real time.
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