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) ...

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 is a preview. Log in through your library . Abstract A dynamic decision problem in which the effect of control action is either delayed for a number of time periods or has an effect that lasts ...

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 paper investigates conditions under which stochastic dynamic programs easily reduce to static deterministic programs. The conditions, though strict, are still rich enough to aid in the solution ...

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 ...