Matt will argue that Optimization can be, and perhaps should be, framed as a sequential decision problem. Viewing optimization this way will let us unify Testing, Targeting, and even Attribution, as interrelated subtasks. Matt will then introduce Reinforcement Learning, a method from the field of Artificial Intelligence, as a general approach to find optimal policies over multi-touch problems. Note: This talk will be mostly conceptual. I will however provide a list of resource for those interested in learning more. If you are looking for a 'three practical skills to bring back to the office on Monday' talk, you may want to skip.