Dynamic programming algorithms are a good place to start understanding what's really going on inside computational biology software. The heart of many well-known programs is a dynamic programming ...

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 ...

This paper develops a formalism within which the application of dynamic programming to discrete, deterministic problems is rigorously studied. The two central concepts underlying this development are ...

Finite horizon sequential decision problems with a "temporal von Neumann-Morgenstern utility" criterion are analyzed. This criterion, as developed in [7], is a generalization of von ...

Mathematical Background: We expect that the student is comfortable with basic mathematics at the level of a U.S. first-year college STEM student. This includes basic notions such as sets and functions ...