Evolving a Learning Machine by Genetic Programming
Eva Alfaro-Cid, K.C. Sharman, Anna Isabel Esparcia-Alcázar · 2006
We describe a novel technique for evolving a machine that can learn. The machine is evolved using a Genetic Programming (GP) algorithm that incorporates in its function set what we have called a "learning node". Such a node is tuned by a second optimization algorithm (in this case Simulated Annealing), mimicking a natural learning process and providing the GP tree with added flexibility and adaptability. The result of the evolution is a system with a fixed structure but with some variable parameters. The system can then learn new tasks in new environments without undergoing further evolution.