Dynamic programming is a technique related to divide and conquer for situations where there may be overlapping subproblems in the recursion. The idea here is to reuse the answers to such sub-problems. This algorithm design concept is illustrated by weighted interval scheduling, segmented least squares, knapsack, RNA secondary structure, sequence alignment, and the shortest path problem.

Recorded lectures:

• “Weighted interval scheduling” please watch until 1:07:30
• “Segmented least squares”   last slide gives information to TU Delft students
• “Knapsack problem” please watch until 45:00
• “RNA secondary sructure” please watch until 1:19:30
• “Sequence alignment”  last slide gives information to TU Delft students
• “Sequence alignment in linear space”  last slide gives information to TU Delft students
• “Shortest paths”  please watch until 46:50
• “Distance vector protocol”  please watch until 52:10

Slides:
Slides with thanks to Kevin Wayne and Pearson Education (made available together with the book “Algorithm Design” by Kleinberg & Tardos)