Building on the recent successes of approximate dynamic programming (ADP) for road-based applications within the transportation community, we develop an ADP procedure to generate good solutions to ...

The paper solves the stochastic inverse optimal problem. Dynamic programming is used to transform the original problem into a differential equation. Such an equation is well-defined (with probability ...

This course covers reinforcement learning aka dynamic programming, which is a modeling principle capturing dynamic environments and stochastic nature of events. The main goal is to learn dynamic ...