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

This is a preview. Log in through your library . Abstract The multi-item joint replenishment problem is generalized to allow ordering costs to be dependent on the specific items jointly supplied. A ...

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 ...

Dynamic Programming and Optimal Control is offered within DMAVT and attracts in excess of 300 students per year from a wide variety of disciplines. It is an integral part of the Robotics, System and ...

This is an advanced undergraduate course on algorithms. This course examines such topics as greedy algorithms, dynamic programming, graph algorithms, string processing, and algorithms for ...

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 ...

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 ...

In addition to other methods we’ve discussed, a third type of variable spending model uses dynamic programming methods. These methods rely on complex computing power and mathematical equations to ...