This course covers basic algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms. It concludes with a brief introduction to intractability (NP-completeness) ...

Dynamic optimization and optimal control problems form the backbone of numerous applications in engineering, economics and the natural sciences. These methodologies involve determining a time-varying ...

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 ...

The background for this paper is a dynamic programming model with a Borel state space and compact action sets. A new simple proof of the compactness of a space of measures corresponding to randomized ...

We introduce a novel approach to solving dynamic programming problems, such as those in many economic models, on a quantum annealer, a specialized device that performs combinatorial optimization.

Management Science, Vol. 31, No. 4 (Apr., 1985), pp. 422-434 (13 pages) A model for measuring the economic benefits of irrigation system development over a depleting aquifer is presented, along with ...