Summary Cont.

• GAs most commonly been applied to optimization problems outside machine learning - especially suited to learning tasks where hypotheses are complex and the objective to be optimized may be an indirect function of the hypothesis (e.g., the acquired rules successfully controls a robot).
• Genetic Programming is a variant of GA where the hypotheses are programs. Demonstrated to learn programs to simulate robot control and recognize objects in visual scenes.