When you think of McDonald’s, the Golden Arches, a Big Mac, or a favorite Happy Meal memory likely spring to mind; but you might not immediately think of the McDonald’s App.  The US Digital team is working to change that.  McDonald’s is transforming their business, driven by digital.  From revolutionizing ordering to personalizing offers, the US Digital team is using data and technology to improve the customer experience and drive sales growth.  Come listen to Hashim Amin, Head of Digital – US Market, speak about McDonald’s digital journey.

We study the problem of fairly allocating a set of indivisible items among $n$ agents. Typically, the literature has focused on one-shot algorithms. In this talk we depart from this paradigm and allow items to arrive online. When an item arrives we must immediately and irrevocably allocate it to an agent. A paradigmatic example is that of food banks: food donations arrive, and must be delivered to nonprofit organizations such as food pantries and soup kitchens.

Policy gradient methods for reinforcement learning and continuous control are popular in practice and have helped recent advances in robotic navigation and in game playing. However, they lack theoretical guarantees even for the simplest case of linear dynamics and a quadratic cost, the Linear Quadratic Regulator (LQR) problem. A difficulty is that unlike the classical approaches to LQR, these methods must solve a nonconvex optimization problem to find the optimal control policy.