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) .

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

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 ...