IEMS 469: Dynamic Programming VIEW ALL COURSE TIMES AND SESSIONS Prerequisites Basic knowledge of probability (random variables, expectation, conditional probability), optimization (gradient), ...

It 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 algorithms are developed for optimal capital allocation subject to budget constraints. We extend the work of Weingartner [17] and Weingartner and Ness [19] by including multilevel ...

Instructors of a new self-paced version of Introduction to Computer Programming found that three weeks before the end of classes, about half of the students enrolled were halfway through the course ...

Richard M. Karp, Michael Held, Finite-State Processes and Dynamic Programming, SIAM Journal on Applied Mathematics, Vol. 15, No. 3 (May, 1967), pp. 693-718 ...