Dynamic programming (DP) algorithms have become indispensable in computational biology, addressing problems that range from sequence alignment and phylogenetic inference to RNA secondary structure ...

We present a novel linear program for the approximation of the dynamic programming cost-to-go function in high-dimensional stochastic control problems. LP approaches to approximate DP have typically ...

Many sequential decision problems can be formulated as Markov decision processes (MDPs) where the optimal value function (or cost-to-go function) can be shown to satisfy a monotone structure in some ...

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 ...

Description: Focuses on the application of the tools of dynamic optimization to problems in economics. Covers continuous-time and discrete-time dynamic optimization techniques, including the calculus ...

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...

Dan Zhang and Larry Weatherford. 2017. Dynamic Pricing for Network Revenue Management: A New Approach and Application in the Hotel Industry. INFORMS Journal on Computing, 29(1): 18-35. Dynamic pricing ...